BRAIN GAIN IN SOUTHEAST EUROPE: MISSION (IM)POSSIBLE? Mirjana Stankovic, PhD Milena Ristovska, PhD c.
Theory Brain drain International transfer of human capital Large scale migration of highly educated/qualified labor force from developing to developed countries
Theory Negatively impacts sending country’s human capital accumulation and fiscal revenue Powerful force in economic development via remittances, trade, FDI, and knowledge transfer
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
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
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
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
Reasons for Brain Drain Innovation system indicator: Low levels of Gross Expenditure on R&D in different sectors
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.
GERD, % of GDP Developed countries
GERD, private sector %
GERD, academia %
GERD, public sector %
Emigration rates by educational level 1995–2005, selected SEE countries
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 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
Possible solutions
Brain Circulation? What are the main reasons for highly educated Diaspora to engage in brain circulation?
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
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
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.
Remittances: Do they matter in the context of brain drain?
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?
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.
Analysis of Remittances Levels in SEE
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
Remittances Inflows to SEE from Migrants with Tertiary Education Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations9 ANOVA dfSSMSFSignificance F Regression Residual Total Coefficients Standard Errort StatP-valueLower 95%Upper 95%Lower 95.0%Upper 95.0% Intercept log(Migration) log(GDP PPP) log(PCGDP PPP) GDP growth rate Fin. sector develop HIGH EDU
Remittances Inflows to SEE from Migrants with Secondary Education Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations9 ANOVA dfSSMSF Significance F Regression Residual Total Coefficients Standard Errort StatP-valueLower 95%Upper 95% Lower 95.0% Upper 95.0% Intercept log(Migration) log(GDP PPP) log(PCGDP PPP) GDP growth rate Fin. sector develop MID EDU
Remittances Inflows to SEE from Migrants with Primary Education Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations9 ANOVA dfSSMSF Significance F Regression Residual Total Coefficients Standard Errort StatP-valueLower 95%Upper 95%Lower 95.0%Upper 95.0% Intercept log(Migration) log(GDP PPP) log(PCGDP PPP) GDP growth rate Fin. sector develop LOW EDU
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.
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).
Thank you!