Brain Drain

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Brain Drain in Islamic Countries: How to Reverse? Dr. S. M. Ali Akkas PhD Email: [email protected], [email protected] Web: www.cdss.ingeniousbd.org

1. Meaning and Measurement Brain drain refers to a one-way flow of highly skilled and educated people moving from their home country to another in search of better jobs, pay, or living conditions. It is differentiated from brain exchange, which implies a two-way flow of highly skilled individuals between a sending and receiving country, and brain circulation, which refers to the cycle of moving abroad to study or acquire skills in one country and then returning home to work.1 Alternatively speaking, brain drain or human capital flight is an emigration of trained and talented individuals ("human capital") to other nations or jurisdictions, due to wage differentials, lack of opportunity, conflicts, health hazards where they are living, discrimination or other reasons. It parallels the term "capital flight" which refers to financial capital that is no longer invested in the country where its owner lived and earned it. Investment in higher education is lost when a trained individual leaves and does not return.2 This phenomenon is widespread in most developing nations, particularly in Muslim countries. Docquier and Marfouk (2006) defined brain drain in terms of skilled emigrants as a proportion to stock of skilled population living in a country. Denoting Nj t;s as the stock of individuals aged 25+, of skills, living in country j, at time t, the emigration rates is defined by: .j M t,s mj t,s = .j Nj t,s +M t,s In particular, mj t;h provides some information about the intensity of the brain drain in the source country j. It measures the fraction of skilled agents born in country j and living in other OECD countries. Before Docquier and Marfouk (2006), a numerous case studies and anecdotal evidences (Carrington and Detragiache 1998, 1999; Adams 2003; Beine, Docquier, and Rapoport 2003; Commander, Kangasniemi, and Winters 2004; Docquier and Rapoport 2004) are available, but without systematic empirical assessment of the brain-drain magnitude. Docquier and

Marfouk presented a comparative structure of brain drain worldwide between groups of countries in terms of their income level, geographical location, and also region of special interest, such as Islamic counties under OIC compared to other groupings. The latest work as a refinement to Docquier and Marfouk’s calculation of skilled migration appears in a recent study by Docquier and Hillel Rapoport (May 2007). Table-1 & 2. The methodology and data sources used in Docquier and Marfouk (2006) study are the computation of emigration stocks and rates by education attainment in origin country in Copyright © 2000-2009 CDSSNet

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1990 and 2000.3 In this computation, migrants of all working-age foreign-born individuals living in an OECD country have been counted. Skilled migrants are those who have at least tertiary education attainment wherever they completed their schooling. The methodology proceeds in two steps: first, computing emigration stocks by education attainment from all countries of the world; and then, evaluating these numbers in percentage of the total labor force born in the sending country (including the migrants themselves).4 Docquier and Marfouk (2006) collected data on the immigration structure by education levels and country of birth from most OECD countries in 1990 and 2000. They published emigration rates by education level for 195 countries in 2000 and 174 countries in 1990. Their estimates address two of the problems arising from the Carrington and Detragiache (1998, 1999) database: under-reporting for small countries and transposition of the US immigration education structure to the rest of the OECD countries (and, in addition, they provide data for a second year, 2000). To take care of these problems, Beine, Docquier and Rapoport (2007a), building on Carrington and Detragiache estimates, used immigrants’ age of entry as a proxy for where education has been acquired. They provide alternative measures of the brain drain by defining skilled immigrants as those who left their home country after age 12, 18 or 22, and to do so for 1990 and 2000. (Table-2).

2. Size, Structure and Destinations of Brain Drain 2.1 Magnitude of Migration in the Past Data available on size and the education structure of international migration suggest that brain drain is now much more extensive than it was two or three decades ago. The number of highly skilled emigrants from Africa increased from 1,800 a year on average during 1960–75 to 4,400 during 1975–84 and 23,000 during 1984–87 (Haque and Jahangir, 1999). The trend continued in the 1990s in the face of the increasingly “quality-selective” immigration policies followed in many OECD countries. Since 1984, Australia’s immigration policy has officially privileged skilled workers, with candidates being selected according to their prospective “contribution to the Australian economy.” New Zealand Immigration Policy 1991 was a shift from a traditional “source-country preference” toward a “points-system” selection, similar to that in Australia (Statistics New Zealand 2004). The similar Canadian immigration policy resulted in higher share of highly educated people among the selected immigrants. For example, in 1997, 50,000 professional specialists and entrepreneurs immigrated to Canada with 75,000 additional family members, representing 58 percent of total immigration. Since the Immigration Act of 1990, USA emphasizes selection of highly skilled workers through a system of quotas favoring candidates with academic degrees or specific professional skills. The annual number of visas USA issued for highly skilled professionals (H-1B visas) increased from 110,200 in 1992 to 355,600 in 2000. EU countries are also leaning toward becoming quality selective. As reported in Lowell (2002a), “European Commission President Prodi has called for up to 1.7 million immigrants to fill an EU-wide labor shortage through a system similar to the US green cards for qualified immigrants.” A growing number of EU countries (including France, Copyright © 2000-2009 CDSSNet

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Germany, Ireland, and the United Kingdom) have recently introduced programs aiming at attracting a qualified labor force especially in the field of ICT through the creation of labor-shortage occupation lists (Lowell 2002b).

2.2 World Migration and Brain Drain — an Overview Docquier and Marfouk (2006) database provides an estimated total number of adult immigrants living in the OECD area aged 25 or more at 59 million for 2000 and 41.8 million for 1990 (Table-3). In 2000, individuals with tertiary education were 36% of the immigrant population in OECD countries, while those with primary education were 35%. The OECD emigration rates by education levels are 1.1%, 1.8% and 5.4% respectively for low-skill, medium-skill and high-skill workers. According to the United Nations (2002), between 1990 and 2000 the number of individuals living outside of their country of birth increased from 154 million to 175 million, reaching a level equivalent to 3% of the world population. At the world level in 2000, highly skilled immigrants represented 34.6 percent of the OECD immigration stock, while only 11.3 percent of the world labor force had tertiary education. Between 1990 and 2000, the percentage of skilled workers among immigrants increased by 4.8 percentage points (from 29.8 percent to 34.6 percent). In 2000, the number of migrants with tertiary education living in the OECD countries amounted to about 20.4 million, of which 2.4 million came from Islamic countries (11.9%). The share of migrants who completed their secondary school degree increased from 25.3 to 29.0 percent. Consequently, low-skilled migration becomes increasingly less important in relative terms (44.9 percent in 1990 and 36.4 percent in 2000). In absolute terms, the size of all groups has increased. More than 85 percent of OECD skilled immigrants live in the six largest immigration countries. About half (50.7%) of these immigrants are living in the United States; 13.4 percent live in Canada, 7.5 percent in Australia, 6.2 percent in the United Kingdom, 4.9 percent in Germany, and 3 percent in France. Contrary to other major receiving countries, the proportions of high-skilled migrants have decreased in Canada and Australia between 1990 and 2000. Between 1990 and 2000, the share of immigrants in the US population increased from 8% to 11% and in the EU population increased from 5% to 7% (Docquier and Marfouk, 2006). Grogger and Hanson (2007) mentions while North American attracts only 38% of emigrants with primary education, USA and Canada attracts 66% of emigrants with tertiary education. In Europe, the shares are flipped, as it attracts 22% of emigrants with tertiary schooling but 53% of emigrants with primary schooling. Between 1990 and 2000, the number of highly skilled emigrants from OECD countries increased less than the number of working-age highly skilled residents. The average emigration rate of OECD highly skilled workers decreased from 4.1 to 4.0 percent. Regarding non-OECD countries, the number of highly skilled emigrants increased more than the number of highly skilled residents. The skilled migration rate increased from 6.6 to 7.2 percent in non-OECD countries. The same rate as a whole for Islamic countries is 7.1%. This shows aggravation in brain drain situation in developing as well as Muslim countries.

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The most affected regions by rate of skilled migration are the Caribbean (42.8%) and areas in the Pacific Oceania (Micronesia 44.0%, Melanesia 32.3% and Polynesia 75.2%), which are groupings of small islands. Other remarkable areas are Eastern Africa (18.6%), Middle Africa (16.1%) and Central America (16.9%). The difference between skilled and total emigration rates is especially strong in Africa (10.4%, 1.5%). This is essentially the result of the low level of education in that part of the world (Frédéric Docquiera and Hillel Rapoport May 2007).

32.7

35.6

38.4

45.1

52.5

47.9

56.2

Za m bi a

16.8

17.0

17.2

M or oc co

C am er oo n

17.7

23.3

S en eg al

A fg an is ta n

G ua te m al a

In %

24.2

G uy an a G am bi a M au ri t S iu ie s rra Le on e S ur in am M oz e am bi qu e K en ia U ga nd a S om al ia

In %

63.3

89.0

The share of Islamic countries in the OECD immigration stock is 14.4%, of which 11.9% belong to skilled category (Table-4). Fig-1: Islamic Countries with High Skilled Emigration Rate While total emigration rate of Islamic countries is 1.6%, the rate of skilled 100.0 80.0 emigration is 7.1%. Whereas the share of 60.0 Series1 40.0 skilled workers among residents in Islamic 20.0 countries is 5.9%, the share of skilled 0.0 workers among migrants is as high as 28.7% compared to Asia (46.8%), Oceana (45.0%) and Africa (30.9%), Sub-Saharan Africa (42.6%), UN least Developed Countries (34.0%), UN Land Locked Developing Countries (37.0%), UN Small Island Fig-2: Islamic Countries with Moderate Skilled Developing Countries (37.6%), Emigration Rates European Union-15 (32.5%). Of 30.0 25.0 course, Arab countries (a subset of 20.0 Islamic countries) are more affected 15.0 Series1 10.0 by the brain drain than Islamic 5.0 0.0 countries as a whole (Arab skilled emigration rate 7.8% compared to 7.1% of Islamic countries).

0.7

0.6

0.4

0.2

Kyrgizstan

Oman

Tazikstan

Turkmenistan

0.7

Uzbekistan

1.2

0.9

Maldives

Saudi Arabia

1.2

Kazakhstan

2.1

2.0

Lybia

Indonesia

2.4

Chad

Azarbizan

2.6

2.4

Burkina Faso

4.6 Egypt

Bangladesh

In %

4.3

When compared the individual country position, Guyana, one of the Islamic countries, tops in the world with the Fig-3: Islamic Countries with Low Skilled highest rate of skilled Emigration Rates emigration. Among the 5.0 4.5 Middle and Low-income Top4.0 3.5 30 Skilled Emigrant 3.0 Series1 2.5 2.0 Countries, in terms of highest 1.5 1.0 skilled emigration rate, 8 are 0.5 0.0 st Islamic: Guyana (89.0%, 1 ), Gambia (63.2%, 15th), Mauritius (56.1%, 17th), Sierra Leone (52.5%, 19th), Suriname (47.9%, 20th), Mozambique (45.1%, 22nd), Kenya (38.4%, 26th), and Uganda (35.6%, 29th) – six being in the lower-15 echelon (Table-5). Among the Top-30 highest stock of skilled emigrants countries, 7 are Islamic: Iran (308774, 8th), Pakistan (222534, 14th), Turkey (174437, 16th), Copyright © 2000-2009 CDSSNet

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Egypt (150596, 22nd), Nigeria rd (149528, 23 ), Morocco (141238, 25th), and Guyana (118263, 30th). Among the Lowest-30 Emigration Rate Countries, 12 Islamic countries are: Turkmenistan (0.2%, 1st), nd Tajikistan (0.4%, 2 ), Oman (0.6%, 4th), Uzbekistan (0.7%, 6th), Kyrgyzstan

Fig-4: Stock of permanent Egyptian migrants by receiving country, 2002

(0.7%, 7th), Maldives (1.2%, 9th), Kazakhstan (1.2%, 10th), Azerbaijan (2.0%,12th), Indonesia (2.1%, 13th), Libya (2.4%, 16th), Chad (2.4%, 18th), Burkina Faso (2.6%, 20th). (Table-5. source: Docquier and Marfouk, 2006). Here out of twelve Islamic countries, nine are within the lowest-15 emigration rate countries.

That means, Islamic countries as a group representing 30% countries of the world are less than one-fourth of the most suffered 30 countries, and queued mostly in the bottom half of the listed countries. Within the least suffered 30 countries, 40% are the Islamic countries mostly queued in the bottom half of the listed lowest emigration rate countries (Table-5). This echoes the comment of Docquier and Marfouk (2006) that the Islamic countries as a whole are not strongly affected by brain drain.

3. Brain Drain: Cost and Benefit 3.1 Gains and Losses in OECD Countries On the whole, OECD countries benefit from the international mobility of skilled workers. The net gain (defined as the net immigration of skilled workers, expressed in percentage of the working-age resident population) amounts to 1.6 percent in 2000, compared with 1.0 percent in 1990. The net brain gain has globally improved in all OECD countries. Hence, the 1990 balanced situation in Scandinavian countries turned into a net brain gain in 2000. The EU-15 deficit turned into a quasi-balanced situation. The main winners of this brain gain between 1990 and 2000 are Australia (11.4%), Canada (10.7%), and Luxembourg (7.3%) followed by the United States (5.4%),

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Switzerland (3.8%), and New Zealand (2.9%). Conversely, Ireland, Greece, and Portugal experienced a brain loss of 2 percent (Docquier and Marfouk, 2005).

3.2 Costs for the Source Countries The brain drain increases the scarcity of highly needed skilled labour in developing countries and consequently reduces long-run economic growth and income. In addition, if highly educated workers continue to immigrate to richer countries, public funds spent on higher education in order to promote growth may be to a large extent inefficiently applied.5 The proposition is subscribed by a study when it says, if emigration promotion reduces relative supply of skilled labor, it could adversely affect developing countries (Bhagwati and Hamada, 1974). Conservatively speaking, Brain drain has cost the African continent over $4 billion in the employment of 150,000 expatriate professionals annually mostly in Muslim countries.6 According to UNDP, Ethiopia lost 75 per cent of its skilled workforce between 1980 and 1991 which harms the ability of such nations to get out of poverty. Nigeria, Kenya and Ethiopia are believed to be the most affected. In the case of Ethiopia; while the country produces a lot of very good doctors, there are more Ethiopian doctors in Chicago than there are in Ethiopia.7 Among the countries of Asia and the Pacific, Iran lost 150,000 people per year.8 Most of the people in Malaysia opt to migrate to Singapore, Australia and New Zealand believing that they will have a better life than if they stay in Malaysia. There are more than 300 000 Surinamers, mostly highly educated, living in the Netherlands, the number is as high as the number of people in Surinam itself. In 2005, eighty percent of Haitians and Jamaicans with college degrees live outside their country.9 3.3 Brain gain: A home benefit It is the usual analysis that brain drain benefits destination country with the amount of talented manpower for which she did not have to make any investment. As regards source country brain drain might have been compensated somewhat by the remittances it receives from the destination countries. According to the World Bank close to 200 million people are living outside of their home countries, with remittances estimated to reach about US$ 225 billion in 2005. The World Bank's Chief Economist and Senior Vice President for Development Economics, François Bourguignon says the household survey evidence presented in the report demonstrates a direct link between migration and poverty reduction. Regardless of the type of migrant - educated or not - reports show that the money the migrants send back home does help alleviate poverty in their former home. (World Bank, 2006. Global Prospects). A survey of Filipino households shows the remittances they receive mean less child labor, greater child schooling, more hours worked in self employment and a higher rate of people starting capital intensive enterprises. In the Guatemala case study, remittances reduced the level and severity of poverty. The biggest impact was on the Copyright © 2000-2009 CDSSNet

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severity of poverty, with remittances making up more than half the income of the poorest ten percent of families. The report shows the money migrants sent back to Guatemala was spent more in investments - such as education, health and housing, rather than on food and other goods.10

4. Causes and Consequences of Brain Drain 4.1 Causes Part of the explanation of widespread migration creating brain drain for source countries may be due to pull factors such as wage differentials, differences in the quality of life, and educational opportunities for children and job security in the destination countries.11 Among the push factors included are adverse political situation, health hazards etc. One explanation for the preponderance of the skilled among emigrants from poor countries is that the income gain from emigration is higher for these individuals. With large differences in base wages between labor-exporting and labor-importing countries, the more skilled will have a relatively strong incentive to emigrate. (Gordon H. Hanson, 2007). This is supported by empirical evidences when Hanson reports that in 2000 the average hourly wage for a male with six to eight years of education was $2.30 in Mexico and $8.80 among recent Mexican immigrants in the United States (Hanson, 2006); and the preference of high-skilled emigrants for North America over Europe is reflected with Canada and the U.S. having high rewards for skill relative to continental Europe – an evidence shown in the work of Grogger and Hanson (2007). Using various regression models, Docquier, O. Lohest and A. Marfouk put forward the determinants of brain drain and explain cross-country differences in skilled migration. Unsurprisingly, they have found that brain drain is strong in small countries which are not too distant from the major OECD regions, which share colonial links with OECD countries and which send most of their migrants to host countries where quality-selective immigration programs exist. More interestingly, the brain drain increases with political instability and the degree of fractionalization at origin; it globally decreases with natives 'human capital. (F.

Docquier, O. Lohest and A. Marfouk, 2007). The factors contributing to the flight of trained medical personnel from country experiences such as Ghana include low salary and remuneration, poor long-term career prospects, the low respect/value placed in health workers by Ghana's medical system, poor management of the health system, and bleak prospects for saving enough money for retirement. At the same time, demand for doctors and nurses has increased in countries that do not produce enough of their own medical professionals. Other factors influencing brain drain may include population size, income level and geographical location and degree of openness of the country. The international mobility of skilled workers is a crucial issue for middle-, low-income and Islamic countries, mainly because their share of tertiary educated workers remains low compared with high-income countries. Antecol, Cobb-Clark, and Trejo (2003) also confirm these Copyright © 2000-2009 CDSSNet

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results by comparing the stock of immigrants who arrived after 1985 in the United States, Canada, and Australia. They show that low-income countries have been strongly affected by the recent brain drain. In all OECD areas, the percentage of skilled immigrants coming from low-income countries (such as India, China, Vietnam, Pakistan, and Indonesia) increased between 1990 and 2000, especially in North America. Table-1 shows that size of population of the country has impact on brain drain. Regarding size groups, the share in the OECD stock is obviously increasing with the country size. It is noteworthy that the share of lower-middle-size countries exceeds the share of upper-middle-size countries. In relative terms, a decreasing relationship between emigration rates and country population sizes is found. The average rate in small countries is seven times larger than the average rate in large countries. Smaller countries simply tend to be more open to migration. Hence, differences in skilled migration are more or less proportional to differences in total migration rates. This explains why small island developing countries exhibit particularly high migration rates while landlocked countries exhibit lower rates. Table-1 further shows that as for income groups, their share in the OECD stock is variable. Nevertheless, the highest average rates are clearly observed in middle-income countries. High income countries (less incentives to emigrate) and low-income countries (where liquidity constraints are likely to be more binding) exhibit the lowest rates. As reported in Schiff (1996), liquidity constraints in poor and unequal societies explain the increasing relationship between income and migration at low-income levels. Papers by Freeman (1993), Faini and Venturini (1993), Funkhouser (1995), and World Bank (1994) have shown that emigrants essentially do not come from the low-income group. Nevertheless, the reality is more complex than this global picture shows. Sub-Saharan African countries and the least developed countries exhibit a high rate of skilled migration (13 percent). The latter groups exclude large low-income countries (such as India, China, and Indonesia) with low emigration rates. While our indicators suggest that country size and gross domestic product (GDP) per capita are potential determinants of emigration, formal tests are required to assess their real contribution, as well as the relative effect of selection policies; networks; and economic, cultural, historical, or political determinants of emigration. Whether these push-and-pull factors play differently across skill groups is a crucial issue. (Docquier and Marfouk, 2005).

4.2 Consequences of Brain Drain Consequences of brain drain are mixed, positive and negative both. Early literature debated over the welfare effects of a brain drain, with some consensus that global welfare is raised by the rational choice of highly skilled emigrants to seek improved incomes abroad (Johnson, 1967; Berry and Soligo, 1969). 6 However, subsequent works warn that brain drain has adverse effects on sending country development. In particular, high levels of skilled emigration slow economic growth and, adversely affect those who remain. As a consequence poverty and inequality are likely to increase (Bhagwati and Hamada, 1973). 7

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More recent economic theory predicts that high skilled emigration reduces economic growth rates. Indeed, research finds that the average level of human capital in a society has positive effects on productivity and growth. One study of 111 countries covering 1960 to 1990 finds that a one-year increase in the average education of a nation’s workforce increases the output per worker by between 5 and 15 per cent (Barro and Sala-I-Martin, 1995; Topel, 1998).8 Conversely, low average levels of education can slow economic growth, damage the earnings of low-skilled workers, and increase poverty (Lowell and Findlay, 2001). About twenty years later, the first papers to investigate the migration human capital formation relationship in an endogenous growth framework rested on similar arguments and also emphasized the negative effects of the brain drain (e.g., Miyagiwa, 1991, Haque and Kim, 1995). A third generation brain drain research emerged since the mid-1990s around the idea that migration prospects can foster domestic enrolment in education in developing countries, raising the possibility for a brain drain to be beneficial to the source country (e.g., Mountford, 1997, Stark et al., 1998, Beine et al., 2001). But there is limited evidence that return migration is significant among the highly skilled. In fact, return migration is characterized by negative self-selection (Borjas and Bradsberg, 1996) and is seldom among the highly skilled unless sustained growth preceded return. Such specific experiences apart, return skilled migration remains relatively limited and is often more a consequence than a trigger of growth in the home country. Beine et al. (2007b) find evidence of a positive impact of skilled migration prospects on gross human capital levels in a cross-section of 127 developing countries. In contrast, Faini (2003) finds a depressing but not significant effect of tertiary emigration on domestic enrolment in higher education, a finding he attributes to the choice of wouldbe migrants to pursue their studies abroad. Migrants’ remittances constitute another channel through which the brain drain may generate positive effects for source countries. The results from empirical studies are mixed. Most micro-studies (e.g., Lucas and Stark, 1985, Cox et al., 1998, Brown and Poirine, 2005) find a positive effect of education on the probability of sending remittances and on the amounts remitted after controlling for income, which suggests that remittances have a loan repayment component. However, at an aggregate level, Faini (2007) shows that migrants’ remittances decrease with the proportion of skilled individuals among emigrants and concludes that “this result suggests that the negative impact of the brain drain cannot be counterbalanced by higher remittances”. The outflow of labor raises wages for workers in source countries (Mishra, 2005; Aydemir and Borjas, 2007) and migrants share income gains with non-migrating family members through remittances. For many small countries, remittances have become a significant source of income. In 2003, remittances exceeded 10% of GDP in the Dominican Republic, El Salvador, Haiti, Honduras, Jamaica, and Nicaragua (IADB, 2004). The Inter-American Development Banks finds that in 2003 in El Salvador, Guatemala, Honduras, and Mexico over 14% of adults received remittances from the United States. In that year, Latin American immigrants in the United States sent a total of $31 billion to their home countries, amounting to 1.4% of the region’s GDP.

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5. Correlation between H.R. development, R&D and the Brain Drain Brain drain is linked to issues such as human resource development (education, training and employment), and to economic growth and social development (social welfare and poverty alleviation). The implication of the link is equally important for Muslim countries. This link is better expressed by Kofi Anan, the then United Nations Secretary General, when he pointed out during a UNESCO international conference on science and technology, the flight of African engineers, professors and medical doctors affecting human resource development.12 The continent is said to have lost many of its best scholars, researchers and professionals. Between 1960 and 1990, it is estimated that Africa lost almost 127,000 highly skilled workers to advanced industrialized countries, including medical doctors, university lecturers, engineers and surveyors. The loss affected African countries in all aspects of its human resource development and promotion of science and technology, and research and development. The ’virtual’ migration of African researchers or scientists, namely who remain in their home countries while working for industrialized countries’ research institutions in fields of endeavour set out by those institutions, is yet another example of the African brain drain. The IOM and UNECA regional conference on the brain drain and capacity building in Addis Ababa (22-24 January 2000) stressed the detrimental effects of the brain drain on science, technology, and social and economic development, and emphasized the need to reverse it into brain gain through the Diasporic option.13

6. Measures for Reversing Brain Drain Brain drain situation of Islamic countries might have some additional dimensions which can be explained by the OECD key players’ role on matters of conflicting interest with Islamic countries: economic and political. How far the antagonism influences immigration policy of OECD countries is a subject of study. However, any interim policy measures to reverse brain drain in Muslim countries should have interventions both at individual country and OIC level. a) Delaying emigration. For example, doctors may be asked to stay on for two years after their training to 'pay back' what they 'owe' to society. A more sophisticated strategy is to incorporate delay within the training period, thus ensuring that certification follows rather than precedes a spell of public service; b) Emigration can be inhibited either in the destination or source countries. The main constraints in the destination countries are the labour market and immigration policies, but at high skill levels another important consideration is the portability of qualifications. Increasingly, this inhibition is falling away as educational franchise operations and international certification expand. Emigration can be inhibited in the source countries by developing special privileges for scarce groups through pay incentives, enhanced research budgets and laboratory and hospital subsidies; c) A relaxed, market-driven solution is to ignore the emigration of skilled workers and let a brain-drain from poorer countries replace lost skills; d) It might be possible to reduce the negative effects of the brain-drain by promoting links with skilled nationals and former nationals abroad;

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e) If a brain-drain begins seriously to affect the quality and delivery of public and private services, two obvious solutions (a) make it worthwhile for highlytrained professionals to stay and (b) replace them with competent locals at a rate faster than their departure; f) Recruiting foreign personnel in key segments. Imported personnel need to be carefully recruited and publicly certified to ensure that their skills meet local standards and induce local confidence in their abilities; g) Return of Talent: For that development of a suitable incentive package has to be developed. h) Developing a brain gain network effectively encouraging the Diaspora in contributing to development at home. (For example 80 per cent of recent foreign investment in the People's Republic of China came from overseas Chinese). B. Measures under OIC The empirical findings show that OIC developing countries should spend more of their national resources on improving human capital (e.g., on education and training). The increased demand for technically skilled labor in contemporary economies has made improved human capital an essential ingredient in any ambitious economic development plan. Of course, the desirable growth objectives from such human capitalpromoting policies would most likely materialize in an atmosphere of political stability and reforms (Abdel-Hameed M. Bashir and Ali F. Darrat, 1994). OIC as intergovernmental body has adopted a new vision in reversing brain drain in Muslim countries. The vision include: system-wide education reform in Member States, including increased gender parity and access to primary and secondary education, review and overhaul of the existing curricula to place greater emphasis on science and Information and Communication Technology (ICT), greater investment on Research and Development (R&D) to reverse brain-drain and inter-agency cooperation to elevate the standards of existing institutions at all levels. To shed light on the brain-drain of competent professionals, particularly in the sciences, from the Islamic World to the West and to coordinate actions with Muslim competencies abroad, the OIC New Vision has set forth the exploration of strategies for the establishment of an International Islamic Centre for Scientific Research and deliberations under which 20 universities from the Islamic World have selected with a view to promote their advancement to the echelons of the top 500 universities in the world. To promote R&D programs in Member States, the New Vision has outlined a strategy whereby each country will contribute at least 1% of its Gross Domestic Product (GDP) to R&D initiatives. There is also greater emphasis upon public and private national research institutions to invest in technology capacity-building and establish and extend Venture Capital Funds. In the realm of inter-agency cooperation to improve ICT standards and reduce the digital gap between Developed and Developing States, a series of joint programs and projects are currently underway between OIC entities including the Islamic University of Technology (IUT), Islamic University of Niger (IUN), SESRTCIC and ISESCO and UN entities including the International Telecommunications Union (ITU), United Nations International Development Copyright © 2000-2009 CDSSNet

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Organization (UNIDO), UNDP, UNESCO and UNIFEM. Such projects incorporate the exchange of ICT related data, cooperation on capacity building and ICT indicators, joint research programs, courses and seminars, tele-education, digitalization of libraries, creation of documentation centres, support for vocational and technical education and the participation of women in ICT. Additionally, to improve the performance of the four OIC-affiliated universities in Bangladesh, Malaysia, Niger and Uganda, a Memorandum of Agreement (MoA) was signed between these institutions in 2006 to strengthen collaboration and cooperation on curriculum reform, administration reform and the enhancement of education standards and quality.

7. Conclusion Across the countries data available on migration worldwide provide a comparative position on size and structure of brain drain in Muslim countries. Even though Muslim countries as group are not strongly affected compared to other groups, a good number of the Muslim countries are worst affected by the phenomenon. Some of the theoretical and empirical works explain the causes leading to brain drain. However, these studies provide only economic analysis thus giving only limited information on the causes and consequences of brain drain in Muslim countries. Any complete analysis of the phenomenon should be supplemented by geopolitical and cultural inquiries of the problem.

1 Diehl, Claudia (2005), “New Research Challenges Notion of German Brain Drain”, German Federal Institute for Population Research, Wiesbaden David Dixon, Migration Policy Institute. 2

Wikipedia, Wikimedia Foundation, Inc., a US-registered 501(c)(3) tax-deductible nonprofit charity.

3

The 2000 data set distinguishes 192 independent territories (Vatican City and the 191 UN member states, including Timor-Leste, which became independent in 2002) and 39 dependent territories. Stocks are provided for both types of territories while rates are only provided for independent countries as well as three dependent territories, which are treated as economies—Hong Kong (China), Macao SAR, and Taiwan (China)—and one occupied territory (Palestine). Because most of the Korean migrants to the United States did not accurately report their origin, we cannot distinguish between the Republic of Korea and Democratic People’s Republic of Korea (estimates are provided for Korea as a whole).We distinguish 174 countries in 1990, before the secession of the Soviet bloc, the former Yugoslavia, the former Czechoslovakia, the independence of Eritrea and Timor-Leste, and the German and the Republic of Yemen reunifications.

4 This definition of skilled migrants deserves two main comments. First, the set of receiving countries is restricted to OECD nations. Second, we have no systematic information on the age of entry. It is therefore impossible to distinguish between immigrants who were educated at the time of their arrival and those who acquired education after they settled in the receiving country; for example, Mexican-born individuals who arrived in the United States at age 5 or 10 and graduated from U.S. highereducation institutions are counted as highly skilled immigrants. Hence, our definition of the brain drain is partly determined by data availability. Existing data do not allow us to systematically eliminate foreign-born individuals who arrived with completed schooling or after a given age threshold. 5

Global Statistics (2005), “Brain Drain”, Research Group on the Global Future.

6

http://www.theafricamonitor.com/news/ethiopian/april2007/290407/report.htm

7

http://www.sharingwitness.org/health_welfare/medical_students_beyond_border/

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8

BBC: http://news.bbc.co.uk/2/hi/middle_east/6240287.stm

9

Wikipedia, Wikimedia Foundation, Inc., a US-registered 501(c)(3) tax-deductible nonprofit charity.

10

Wikipedia, Wikimedia Foundation, Inc., a US-registered 501(c)(3) tax-deductible nonprofit charity.

11

Global Statistics (2005), “Brain Drain”· Research Group on the Global Future.

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IOM-UNECA-IRDC 2000: 3

13 Entzinger, H. B., Catherine. Wihtol de Wenden, Marco. Martiniello “The Brain Drain in Selected African Countries” , Migration Between States and Markets.

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Organisation for Economic Co-operation and Development (OECD). 2002. Trends in International Migration. Paris: OECD Editions. Schiff, M. 1996. “South-North Migration and Trade—A Survey.”World Bank Research and Policy Report, no. 1696.World Bank,Washington, DC. Schiff, M. 2005. Brain Gain: Claims about Its Size and Impact on Welfare and Growth Are Greatly Exaggerated. IZA discussion paper, n. 1599. Bonn. Stark, O., C. Helmenstein and A. Prskawetz (1998): Human capital depletion, human capital formation, and migration: a blessing or a ’curse’ ?, Economics Letters, 60, 3: 363-7. Stark, O. and Y. Wang (2002), Inducing human capital formation: migration as a substitute for subsidies, Journal Public Economics, 86(1): 29-46. Wickramasekera, P. 2002, Asian labour migration: issues and challenges in the era of globalization. International Migration Papers, 57, International Labor Office (ILO), Geneva. United Nations. 2001. “Human Development Report 2001.” New York, Oxford: Oxford University Press. ———.2002. “International Migration Report 2002.”New York: United Nations. Vidal, J.-P. 1998. “The Effect of Emigration on Human Capital Formation.” Journal of Population Economics 11(4): 589–600. Wong, K.-Y., and C.K. Yip. 1999. “Education, Economic Growth, and Brain Drain.” Journal of Economic Dynamics and Control 23(5–6): 699–726. World Bank. 1994. “Kingdom of Morocco—Poverty, Adjustment and Growth.” Report 11918-MOR.World Bank,Washington, DC. ———. 2003. World Development Indicators. Washington, DC: World Bank. World Bank. 2006. Global Prospects. Washington, DC: World Bank.

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Tabale 3 International Mobillity by Education Attainment – An Overview

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Table 4 Data by Country Group in 2000

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Table 5 Top-30 Skilled Emigration Countries, 2000

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Table 6 Net brain gain in OECD countries in 2000

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