Riccardo Faini (Università di Roma Tor Vergata, IZA and CEPR)

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Immigration in a globalizing world Riccardo Faini (Università di Roma Tor Vergata, IZA and CEPR)

The conventional wisdom about immigration The net welfare effect of unskilled immigration is at best small Its distributional impact is however substantial Only skilled immigration has a clear positive welfare impact on receiving countries

The bias against unskilled migration A supposedly negative impact on wages and unemployment The lesser scope for redistributive policies The public finance impact A politically and socially divisive issue

Are there too many migrants? (percentage of all answers) Belgium 54.3 France 54.7 Germany 56.7 Italy 64.0 UK 51.3 USA (in 93) 54.5 USA (in 97) 48.0

The viewpoint of sending countries Restrictions on unskilled migration deprives sending countries from a powerful engine for growth and convergence The bias toward skill migration deprives the home country from its most skilled and talented people

The welfare impact in source countries The basic formula: B/B = -(α L m 2 ε)/2 where : B : welfare α L : labour share ε: wage elasticity with respect to employment m: population share of migrants Allowing for remittances : B/B = -(α L m 2 ε)/2 + β m Results: Welfare effects are small For plausible parameter values, B < 0 if m > 0.43

The brain drain migration rates by educational attainments Origin country Secondary Tertiary educ. educ. Korea 3.3 14.9 Philippines 6.0 9.0 Ghana 0.7 25.7 Uganda 0.6 15.5 Dominican Rep. 30.5 14.7 Mexico 20.9 10.3

The revisionist view of brain drain Skilled workers are likely to earn more abroad and, hence, ceteris paribus, remit more The stronger incentive to invest in human capital may more than offset the loss of skilled workers Return migrants may bring home valuable skills that they have acquired abroad

Three basic issues Do skilled workers remit more? They are likely to come from relatively wealthy families Their propensity to remit may be lower Is the brain drain associated with greater education in the home country? Do remittances (and education) boost growth? Remittances may be used unproductively and exacerbate moral hazard problems Remittances may help overcome capital and insurance markets imperfections

Do skilled workers remit more? a simple model Household members belong to one of three groups: R: close members that are reunited with the migrant H: close members that live at home D: distant members Migrant s utility is U(C M,f R ) + f R V C (C R ) + (1-f R ) V C (C H )+V D (C D ) where: C i : consumption of group i f R : percentage of close members that live with the migrant

The key assumptions U f > 0: migrants derive a positive utility from family reunification V C (C) > V D (C) and V C (C) > V D (C): the level and the marginal value of the migrant s utility are relatively larger for the close family members Budget constraints: C M = w (f R R R + (1-f R ) R H + R D ) - θ f R C i = Y i + R i i = R, H, D

The main results Remittances to close family members will be generally higher than those to distant family members If w is up, and reunification is a normal good, then R i and f R will increase Hence, there will be two effects on total true remittances: The wage effect The reunification effect The net effect may well be negative. Only empirical analysis can tell.

Let turn to the empirical section: the data Remittance data come from the IMF: they include workers remittances, compensation of employees, and capital transfers Migration data come from Docquier and Marfouk who extend the work of Carrington and Detragiache

The estimating equation Remittances of group i are: R i = α i w i β i y i i=s,u where: w i = migrant s wage y i = household income Aggregate remittances are: R/P = α U w U M/P + (α S w S - α U w U ) m S /P β U p U y U /Y m U /p U Y/P β S p S y S /Y m S /p S Y/P

The results (1) (2) (3) (4) R/P R/P R/P ln(r/p) M/P 3.7 (2.2) 4.3 (2.4) 3.8 (2.3) 0.36 (8.20) m S /P -1.96 (0.22) -0.9 (0.1) -1.7 (0.2) -0.09 (1.1) m U /p U Y/P 0.15 (2.62) 0.17 (2.8) 0.13 (2.1) -- m S /p S Y/P -0.017 (3.5) -0.025 (3.7) -0.014(1.5) -- m U /p U ln(y/p) -- -- -- -2.49 (4.2) m S /p S ln(y/p) -- -- -- -0.77 (6.3) t M/P 1.2 (0.8) 1.1 (0.7) 3.6 (0.4) 0.02 (1.19) R 2 0.63 0.62 0.63 0.45 NOB 188 188 134 134 Legends R: total remittances, M: migration stock, P: home country s population, m S ( m U ) : skilled (unskilled) migrants, p S (p U ): home country s skilled (unskilled) population, Y: GDP, t: time effect.

The impact of a 10% increase in skilled migration on the GDP share of remittances Caribbean SubSaharan Africa Antigua -1.38 Cote d'ivoire -0.26 Barbados -0.89 Guinea Bissau -0.14 Dominica -1.45 Lesotho -2.86 Grenada -1.41 Mali -0.47 Jamaica -4.77 Mauritania -0.04 Mozambique -0.17 South America Nigeria -0.65 Sudan -0.63 Colombia -0.36 Swaziland -1.02 Ecuador -1.67 Tanzania -0.03 Paraguay -0.59 Uganda -0.61 Peru -0.29 Venezuela -0.06 Asia Bangladesh -0.55 Central America Malaysia -0.11 Mongolia -0.24 Belize -0.86 Nepal -0.23 El Salvador -3.18 Philippines -1.00 Guatemala -0.73 Honduras -1.49 Western Asia Mexico -0.62 Georgia -0.96 Northern Africa Turkey -0.53 Ukraine -0.03 Egypt -0.72 Morocco -1.53 Tunisia -0.92 Source: own calculations based on column 4 of Table 1

The empirics of the brain gain Beine et al. (2001, 2003) Skilled emigration rates as a measure of the probability to move abroad How to measure investment in education? Changes in the average number of years in education? Enrolment rates? Should we distinguish between secondary and tertiary migrants?

Returns to education and the brain drain Dependent variable Secondary school enrolment Tertiary school enrolment Constant -122.9 (-5.82) -60.9 (-11.72) Secondary school migration rate -0.18 (1.04) -- Tertiary education migration rate 0.37 (2.02) -0.11 (-1.79) Income per capita 21.5 (7.32) 9.75 (5.90) NOB 45 51

The impact of remittances (and education) on growth Theory does not provide a clear cut answer as to the impact of remittances on growth Empirical evidence is very divided as to the impact of education on growth Empirical analysis: Decadal growth rates Human and physical capital indicators Policy indicators

Growth and remittances Dep. Var.: growth in per capita GNP (1) (2) ln Y pc (t-1) -0.69 (1.97) -0.77 (2.25) Secondary schooling 0.019 (1.72) 0.024 (2.16) Tertiary schooling 0.019* 0.024* Phone 0.0004 (0.16) 0.0005 (0.02) BMP -1.17 (2.65) -1.24 (2.88) Policy 0.90 (4.9) 0.78 (4.13) Remittances 0.23 (2.25) -- Remittances x -- 0.14 (3.22) Policy R 2 0.85 0.86 S.E. 0.96 0.93 NOB 118 118

The growth effect of the brain drain (a 10 point increase in the rate of skilled migration) (a) (b) The remittance effect (c) -0.23-0.23 The educational effect 0.05-0.03 The aggregate effect -0.18-0.26 (a) allowing for a significant effect of migration probabilities on (net of migration) educational achievements (columns 1 and 2 of table 1) and the positive effect of educational achievements on growth (b) setting the aggregate effect of migration probabilities on educational achievements to zero (c) The effect of the brain drain on remittances is estimated to be negative and equal to 0.1 (a 10 point increase in the rate of skilled migration reduces the remittances to GDP ratio by 1.0 percent of GDP). In turn, the reduction in remittances depresses GDP growth by 1 x 0.23

Conclusions The brain drain is quantitatively large There is limited evidence that favoring skilled immigrants raises the return to education Skilled migration is not associated with a larger flow of remittances Remittances seem to have a positive impact on growth, particularly in countries with good policies Industrial countries policies that favour skilled immigration are at risk of penalizing growth prospects in developing countries. Somewhat perversely, the negative effect of the brain drain will be more strongly felt in those sending countries with a sound policy stance.

A truly global economy? Tight restrictions on unskilled migration Unfettered capital mobility A growing bias in favor of skilled migration

A more symmetric approach to global policy-making? A multilateral framework for labor mobility Adding labor standards to the existing set of codes

Strengthening the fourth pillar: the International Labor Office Broader mandate, including a multilateral framework for migration Expanded surveillance role Additional resources