Global Mobility of Students: An Econometric Analysis of Brain Drain Hypotheses Narender Thakur Department of Economics Bhim Rao Ambedkar College University of Delhi 1

Expanding Global Mobility of Students US and UK are global leaders of quality higher education Harvard University and Cambridge University have first and second ranks respectively in Times and Sanghai Higher education Rankings US and UK are favorite destinations for international students in the time of globalization and global economic crisis Expansion in the global mobility of students in terms of numbers and growth rates In , 0.7 million(690,923) are non-EU students in the UK Out of total non-EU students in the UK, 33 percent are Indians and Chinese(Incidently, 33 % students out of total international students in the US are Indians and Chinese in ). 12 % growth rate of non-EU students in the UK in , 6.3% growth rate of EU students in the UK and 3 % growth rate of UK students in the same year respectively. International students growth rate in the US over the period of was 6.3 % and overall World students in higher education growth rate was 6 %. 2

Research Problem of a Micro Sample Survey of International Students in the Nottingham University Brain-Drain Theories in international and development economics theoretically developed in 1960 s and 1970s, which explained the negative effects of skilled outmigration of professionals to the sending countries (Gruber and Scott, 1966,Hamada and Bhagwati,J., 1975 Bhagwati,J. and Rodriguez,C.1975) The Brain-drain in terms of loss of skilled professionals, low human capital formation, low productivity and production and it eventually lead to lower economic growth in sending countries, mainly to developing economies. In 1990s, there was an emergence of theoretical models of Brain-gain theories(Stark,1990 Mountford,1997 and Vidal,1998). The Brain-gain theories advocated that there are positive effects of skilled migration for the countries of origin because of return migration, remittances, networks and incentives for higher educational investment. The Brain-gain hypotheses were empirically tested with cross sectional data analysis by Beine et. al.(2001) and subsequently with panel data analysis by Beine et. al. (2011). The research problem of the study is to test the Brain-drain or Brain-gain hypotheses with the estimation of probabilities of intentions of return of international students to their home countries after completing education and training in the UK. 3

Hypotheses and Methodology of the Sample-Survey Hypotheses 1.There is positive relationship between age and probability of return of student migrants. 2.The female student migrants have higher chance of return to their countries of origin. 3.High growth performance of the countries of origin has positive impact on the probability of return of the students from the UK. 4.There is a inverse relationship between the probabilities of return of students and source finance of education as scholarship Collection of Data the collection of data, a structured pre-tested questionnaire was used in the sample-survey. The sample size is of 120 respondent students of Nottingham University during academic session , which is a moderate sample size. The ordered probit The ordered outcomes in the questionnaire are used for estimating the probabilities of the likelihood to the return or the stay for the students is as follows: most likely to return (=5), likely to return (=4), Not sure (=3), unlikely to return (=2) and most unlikely to return (=1). 4

Definitions of the Dependent variable and Regressors of Ordered Probit Regression age = Age of students; male=1 if Gender: Male, otherwise=0; growth=1 if High Growth Countries, growth=2 if Moderate Growth Countries and otherwise=0 if Lower Growth Countries; humancapital= 1 if Very High and High Educational Satisfaction=1, otherwise=0; privatefinance=1 if financed by Family or Bank Loans, otherwise=0; bondyears=Number of Bond Years; msc= 1 if Master students, otherwise=0; mscmarket= 1 if Subjects: Economics, Engineering, Science and Business Studies, otherwise =0. 5

Empirical Results of Ordered Probit regression in Micro Sample Survey: Marginal effects Dependent Variable: return Regressors dy/dx (y=5) most likely to returnP>z dy/dx(y=1) most likely to stayP>z age male growth growth humancapital privatefinance bondyears msc Mscmarket

Empirical Results of Ordered Probit Regression and Conclusions 1.The four hypotheses of the study were set to explore the probability of intention to return as dependent variable and explanatory variables age, gender, real Gross Domestic Product growth rates of countries of origin, source of finance, number of bond years, course of studies and marketed-oriented courses. 2.The descriptive analysis and ordered probit regression were employed as the methods. 3. The empirical results show that the probability of return migration of the outside UK born students is 77 percent. 4.The empirical results of four hypotheses have been explained further. - First, probability of return is significantly lower for younger students as they can take more risk in their time preference of higher educational choices when compared to the older students(0.04 points). - Second, the gender-difference is statistically significant with higher probability of return for female students(0.25 points). -Third, the probabilities of return are significantly higher for countries with moderate and higher growth rates of GDP, as compared to the lower growth countries of origin(0.28 and 0.18 points respectively). -Fourth, the probability of return of students with private source of finance is significantly higher in comparison to scholarship holders(0.39 points). 7

Scope for Future Research Moderate sample size of students can be increased and preferably panel data of students’ intentions about the return. In this study, we have studied education sector, an adequate impact of return migration can be analyzed in the labor market. The impact of returned migration of health professionals, IT professionals and teachers in the labor market can be analyzed in future research, especially in developing economies, viz., India. Dynamic panel data analysis, instrumental variable regressions are important econometric methods to solve the problems of endogeneity and omitted- variable bias in future research. 8

Bibliography Beine,M, Docquier,F and Defoort, C. (2011) A Panel Data Analysis of the Brain Gain, World Development, Vol.39,No.4, pp Beine,M, Docquier,F and Rapoport, H. (2003)Brain Drain and LDCs’ Growth: Winners and Losers Discussion Paper No. 819, The Institute for the Study of Labor(IZA). Beine,M. Docquier,F and Rapoport,H(2001) Brain Drain and Economic Growth:Theory and Evidence, Journal of Development Economics,Vol.64,pp Bhagwati, J., and K. Hamada (1974) The Brain Drain, International Integration of Markets for Professionals and Unemployment: a theoretical analysis, Journal of Development Economics, Vol.1, pp Bhagwati,J. and Rodriguez,C.(1975) Welfare-Theoretical Analyses of the Brain Drain, Journal Development Economics, Vol.2,pp Bhargava,A, Docquier and Moullan,Yasser (2011) Modelling the Effects of Physicians Emigration on Human Development, Economics and Human BiologyVolume 9, Issue 2,pp Economics and Human BiologyVolume 9, Issue 2 Gruber, Herbert, and Anthony Scott (1966). The International Flow of Human Capital, American Economic Review, Vol.56, pp

Bibliography HESA (2011) Data Source is the website of Higher Education Statistics Agency, accessed on 4 th of September, IIE(2011) Students/All-Places-of-Origin(Website of Institute of International Education), accessed on September 4,2011http:// Students/All-Places-of-Origin(Website Kim, Jinyoung (1997) Economic analysis of foreign education and students abroad, Journal of Development Economics, Vol. 56 _ –365 Mountford A.,(1997), Can a brain drain be good for growth in the source economy? Journal of Development Economics, Vol. 53, pp Schiff(2005) Brain Gain: Claims About its Size and Impact on Welafare and Gorwth are Greatly Exaggerated, pp Institute for the Study of Labor, IZA, Discussion Paper No Schultz (1961) Investment in Human capital, American Economic Review, Vol.51, No.1, pp Stark, Oded and Galor,Oded(1990) Migrants’ Savings, the probability of return migration and migrants’ performance, International Economic Review,Vol.31,No.2, pp Vidal (1998) The effect of emigration on human capital formation, Journal of Population Economics (1998) Vol.11, pp.58 Zweig,David and Changgui,Chen(1995) China’s Brain Drain to the United States: Views of Overseas Chinese Students and Scholars in 1990s; Berkeley, Institute of East Asian Studies, University of California. 10