1. BRAIN GAIN IN SOUTHEAST EUROPE: MISSION (IM)POSSIBLE? Mirjana Stankovic, PhD Milena Ristovska, PhD c.

2. Theory  Brain drain  International transfer of human capital  Large scale migration of highly educated/qualified labor force from developing to developed countries

3. Theory  Negatively impacts sending country’s human capital accumulation and fiscal revenue  Powerful force in economic development via remittances, trade, FDI, and knowledge transfer

4. Theory  Size of the country and emigration rate are inversely correlated  Average brain drain rates 7 times higher in small countries  Highest emigration rates middle-income countries people have both the motive and the financial means to emigrate

5. Potential benefits  Remittances altruism and loan repayment motive  Return Migration and Brain Circulation  Diaspora Externalities  reduce transaction and other information costs  facilitate trade, FDI and technology transfer between home and host country

6. SEE countries: Brain Drain: Reasons  Dissolution of the past regimes  Weak economic structure  Low level of industrial production  Low performance results of the educational system  High level of public debt  High unemployment level  Lack of motivation, commitment and trust  Corruption

7. SEE countries: Brain Drain: Trends  “External” brain drain = Experts leaving the country for better professional fulfilment abroad  “Internal” brain drain = Specialists leaving their professions for better paid jobs in the private and/or informal sector of the economy

8. Reasons for Brain Drain Innovation system indicator: Low levels of Gross Expenditure on R&D in different sectors

9.  Low level of investments in R&D by the private sector, the academia and the public sector.  Developed countries’ private sector is the key innovation catalyst.  In SEE: academia & public sector have higher investments in R&D.

10. GERD, % of GDP Developed countries

11. GERD, private sector %

12. GERD, academia %

13. GERD, public sector %

14. Emigration rates by educational level 1995–2005, selected SEE countries

15. International skilled migration, estimates controlling for age of entry, percentages Brain drain 0+ years age Brain drain 12+ years age Brain drain 18+ years age Brain drain 22+ years age 19902000 19902000 19902000 19902000 Albania 17,4 14,3 17,3 14,1 17,1 13,9 16,1 13,2 Bosnia & Herzegovina 23,9 23,2 22,9 21,9 Macedonia 29,1 26,9 25,9 24,1 Croatia 24,1 22,1 20,7 18,9 Bulgaria 4,0 6,8 3,9 6,6 3,8 6,5 3,7 6,2 Serbia & Montenegro 13,7 13,3 12,9 12,3 Romania 9,1 11,9 8,7 11,4 8,2 10,8 7,7 10,2

16. Possible solutions

17. Brain Circulation? What are the main reasons for highly educated Diaspora to engage in brain circulation?

18.  Human Development Index (HDI)  Control of Corruption  University-Company Research Collaboration  Availability of Venture Capital  Patent Applications Granted by the USPTO  High-Technology Exports as % of Manufactured Exports  Firm-Level Technology Absorption  Public Spending on Education as % of GDP  Researchers in R&D  Brain Drain  Difficulty of Hiring Index

21. What can the governments do? Establishment of industrial clusters linked to science and university parks Establishment of innovative start– ups by entrepreneurial returnees Promotion of activities by expatriates acting as “transnational professional communities” between the sending and the destination country

22.  Brain drain not as a loss, but a potential gain to the home country.  Challenge: building a sustainable brain circulation network.  Adoption of a regional approach to this issue.

23. Remittances: Do they matter in the context of brain drain?

24. Do highly educated individuals leave with their families, while cutting their ties with their home country and investing back very little or not at all?

25. Determinants of International Remittances  Micro-economic level of analysis – Lucas and Stark (1985), Agarwal and Horowitz (2002), Foster and Rosenzweig (2001), Ilahi and Jafarey (1999).  Migrant workers are motivated to remit for a variety of reasons, ranging from pure altruism to pure self-interest.  Altruistic – migrants’ remittances increase with declines in family income at home  Self-interest motives – remittances are positively related with family income at home.  Macro-economic level of analysis - (El-Sakka & McNabb, 1999; Faini, 1994; Glytsos, 1997; Higgins, Hysenbegasi, & Pozo, 2004).  Macro-economic factors—like interest rates, exchange rates, and political instability— all have an impact on the level of international remittances received by countries. Interest and exchange rates need to be competitive, and that countries need to be politically stable in order to encourage the flow of remittances to labor-sending countries.

26. Analysis of Remittances Levels in SEE

27. Variable nameDescription Source Log of remittances Log of remittances inflows to origin country (current international $) Bilateral Remittances Matrices, The World Bank Log of migrants Log of total number of migrants in selected OECD countries IAB brain-drain data, Institute for Employment Research logGDP Log of GDP expressed in PPP terms (current international $) World Development Indicators, The World Bank LogGDP per capita Log of GDP per capita expressed in PPP terms (current international $) World Development Indicators, The World Bank Expected GDP growth Annual GDP growth (%) World Development Indicators, The World Bank Development of the financial sector Ratio of outstanding deposits with commercial banks to GDP (% of GDP) Balance of Payments Statistics, IMF Number of university-level educated migrants to total migrants Ratio of tertiary educated to total number of migrants (%). IAB brain-drain data, Institute for Employment Research Variable Definitions and Sources

28. Remittances Inflows to SEE from Migrants with Tertiary Education Regression Statistics Multiple R 0.866203721 R Square0.750308886 Adjusted R Square0.001235545 Standard Error0.306007932 Observations9 ANOVA dfSSMSFSignificance F Regression60.562771850.0937953081.0016494310.57760354 Residual20.1872817080.093640854 Total80.750053558 Coefficients Standard Errort StatP-valueLower 95%Upper 95%Lower 95.0%Upper 95.0% Intercept6.40562290611.90161750.5382144830.644312605-44.8029041357.61414994-44.8029041357.61414994 log(Migration)0.8713624322.1263198120.4097983880.721678251-8.27745331310.02017818-8.27745331310.02017818 log(GDP PPP)-0.4117747311.764206738-0.2334050330.837160606-8.0025436687.178994205-8.0025436687.178994205 log(PCGDP PPP)0.3601801044.251672310.0847149260.940204688-17.9332893718.65364958-17.9332893718.65364958 GDP growth rate-0.0044500310.124232859-0.0358200770.974679501-0.538980880.530080819-0.538980880.530080819 Fin. sector develop.0.0103755230.0092369461.123263410.378046053-0.0293678460.050118893-0.0293678460.050118893 HIGH EDU-0.0057234350.041935914-0.1364805230.903939986-0.1861591090.174712238-0.1861591090.174712238

29. Remittances Inflows to SEE from Migrants with Secondary Education Regression Statistics Multiple R0.866403 R Square0.750653 Adjusted R Square0.002614 Standard Error0.305797 Observations9 ANOVA dfSSMSF Significance F Regression60.563030.0938381.0034940.577021 Residual20.1870230.093512 Total80.750054 Coefficients Standard Errort StatP-valueLower 95%Upper 95% Lower 95.0% Upper 95.0% Intercept5.353095.9266930.9032170.461741-20.147430.85359-20.147430.85359 log(Migration)1.1585720.9437081.227680.344451-2.901885.21902-2.901885.21902 log(GDP PPP)-0.6580.812259-0.810090.50295-4.152872.836862-4.152872.836862 log(PCGDP PPP)0.8630631.9880770.4341190.706546-7.690949.417067-7.690949.417067 GDP growth rate0.0083530.0465910.1792920.874228-0.192110.208819-0.192110.208819 Fin. sector develop.0.010080.0101260.9954790.424394-0.033490.053649-0.033490.053649 MID EDU-0.00340.02324-0.146340.897069-0.103390.096592-0.103390.096592

30. Remittances Inflows to SEE from Migrants with Primary Education Regression Statistics Multiple R0.866536 R Square0.750884 Adjusted R Square0.003536 Standard Error0.305655 Observations9 ANOVA dfSSMSF Significance F Regression60.5632030.0938671.0047320.576631 Residual20.186850.093425 Total80.750054 Coefficients Standard Errort StatP-valueLower 95%Upper 95%Lower 95.0%Upper 95.0% Intercept5.6146726.8218160.8230470.497001-23.737234.96658-23.737234.96658 log(Migration)1.0400791.1067620.939750.446548-3.721935.802089-3.721935.802089 log(GDP PPP)-0.557590.908055-0.614050.601726-4.464633.349457-4.464633.349457 log(PCGDP PPP)0.6477282.4748840.261720.818026-10.000811.29629-10.000811.29629 GDP growth rate0.0024560.0723970.0339250.976018-0.309040.313956-0.309040.313956 Fin. sector develop.0.0100850.0099691.0116510.418191-0.032810.052978-0.032810.052978 LOW EDU0.0024350.0159540.1526020.892717-0.066210.07108-0.066210.07108

31. Main Findings from the Empirical Analysis  The impact of migrants’ education level on remittances is negative and significant at the 5% level. The negative sign of the coefficients implies that migrants with tertiary education remit less than less-educated migrants.  The impact of home countries’ financial sector development is positive, though not significant.  The elasticity of remittances with respect to GDP is negative.  The elasticity of per capita remittances with respect to per capita GDP is positive.

32. Implications from the Main Findings  An increase in the share of migrants with tertiary education has a negative impact on total and per capita remittances  This contradicts the claim that the negative impact of the brain drain can be mitigated or even offset by the fact that skilled migrants remit more than unskilled ones.  These findings thus provide an additional source of concern about the brain drain for countries of origin. This should raise the urgency of finding (non-distortive) ways to reinforce skilled migrants’ links with their country of origin. This might possibly be achieved as part of a cooperative arrangement between source and (their principal) host countries, including policies of return and circular migration (Schiff, 2007).

33. Thank you! mirjana.stankovic@fulbrightmail.org milena.ristovska@gmail.com mirjana.stankovic@fulbrightmail.org milena.ristovska@gmail.com