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Selective immigration policies, migrants’ education and welfare at origin
Economics Letters 113 (2011) 19–22
Contents lists available at SciVerse ScienceDirect
Economics Letters journal homepage: www.elsevier.com/locate/ecolet
Selective immigration policies, migrants’ education and welfare at origin✩ Simone Bertoli a,∗ , Herbert Brücker b a
Robert Schuman Centre for Advanced Studies, European University Institute, Via delle Fontanelle 19, I-50014, San Domenico di Fiesole, Italy
b
University of Bamberg, IAB and IZA, Germany
article
info
Article history: Received 9 August 2010 Received in revised form 20 May 2011 Accepted 24 May 2011 Available online 1 June 2011
abstract Destination countries are increasingly adopting selective immigration policies. These can effectively increase migrants’ average education even if one allows for endogenous schooling decisions and education policies at origin. Still, more selective immigration policies can reduce social welfare at origin. © 2011 Elsevier B.V. All rights reserved.
JEL classification: F22 J24 H52 015 Keywords: International migration Selective immigration policies Education policies Social welfare
1. Introduction This paper analyzes the impact of selective immigration policies on migrants’ education and on welfare in the sending country in a model where schooling decisions and education policies at origin are endogenously determined. More and more destination countries are moving toward the adoption of immigration policies which out-select applicants on the basis of human capital criteria.1 The effects of this policy shift depend upon how prospective migrants adjust their schooling choices, and upon the possible changes in public policies toward education at origin. Our analysis draws on the literature on the beneficial brain drain (Mountford, 1997; Stark et al., 1997, 1998; Beine et al., 2001), which is built upon the idea that would-be migrants’
✩ The authors are grateful to an anonymous referee for the comments provided on the paper, and they also thank Sascha Becker, Tito Boeri, Giovanni Facchini, Anna Maria Mayda, Giovanni Peri and to the participants to the fRDB XI European Conference, Pisa, May 2009, for their suggestions; the usual disclaimers apply. Financial support from the NORFACE research programme on Migration in Europe – Social, Economic, Cultural and Policy Dynamics – and from the EU ‘‘Transnational networks of migrants (TOM)’’ Research and Training network is gratefully acknowledged. ∗ Corresponding author. Tel.: +39 0554685873. E-mail address: [email protected] (S. Bertoli). 1 ‘‘Countries that are non-selective and have relatively few highly skilled
immigrats [. . .] may be most likely to demand increased levels of highly skilled migration in the future’’ (OECD, 2009). 0165-1765/$ – see front matter © 2011 Elsevier B.V. All rights reserved. doi:10.1016/j.econlet.2011.05.036
schooling choices respond to the prospect to migrate. In his seminal contribution to this literature, Mountford (1997) argues that selectivity can improve the private incentives to invest in education, as would-be migrants want ‘‘to be eligible for emigration’’. This represents only a part of the story, as policy makers in origin countries do not behave as passive by-standers in the contest for talent, but rather adjust their education policies in response to changes in immigration policies. Such a reaction is induced by the fact that the policy stance at destination can affect the social return to education, as well as the private incentives to bear a larger share of its cost. The model that we propose is related to other papers that analyze the effects of a greater labor mobility on the financing of education (Justman and Thisse, 1997) and on migrants’ average education (Stark and Wang, 2002; Docquier et al., 2008). In contrast to the theoretical models by Stark and Wang (2002) and Docquier et al. (2008), which assume that destination countries adopt general immigration policies that do not outselect applicants with respect to their observable characteristics, our model considers not only the effects of a greater openness but also the effects of a greater selectivity, which is becoming an increasingly salient feature of immigration policies.2
2 In an extension of the model, Stark and Wang (2002) also consider immigration policies that are selective in education, but in a way that does not allow for separately analyzing the effects of selectivity.
20
S. Bertoli, H. Brücker / Economics Letters 113 (2011) 19–22
Our theoretical analysis reveals that a shift toward a more selective immigration policy which keeps the scale of migration unchanged improves the average level of schooling of the immigrants, and of the stayers at origin. While such a policy shift is beneficial for the countries of destination, it can be detrimental for the sending countries, where social welfare could fall. 2. Selective immigration policies and schooling choices We consider a small open economy populated by oneperiod lived agents. We assume perfect credit markets, and no heterogeneity across agents as in Stark and Wang (2002) and Docquier et al. (2008). An agent with s years of schooling earns a wage w0 (s) which is given by
w0 (s) = eω0 (s) = eµ0 +δ0 s .
(1)
We assume that education gives rise to positive externalities, so that the parameter µ0 in (1) is an increasing function of the average level of schooling in country 0, s0 . For the sake of simplicity, we assume a linear relationship between µ0 that and s0
µ0 = ξ0 s0 .
(2)
The time-equivalent cost of acquiring s years of schooling is given by 1 − e−c (s) = 1 − e−γ0 (1−σ0 )s , 2
(3)
where γ0 is a cost-shifter parameter and σ0 is a public education subsidy. The subsidy σ0 is financed with income taxes levied at a rate τ0 on all agents. This entails that the government is able to impose a Bhagwati-tax (Bhagwati, 1979) on migrants, and migration does not give rise to any fiscal loss. The value of τ0 is determined so to keep the fiscal budget balanced. Agents can apply for migration to a foreign country,3 where wages w1 (s) follow
w1 (s) = eω1 (s) = eµ1 +δ1 s .
(4)
We assume that µ1 > µ0 , while we do not introduce any assumption on the domestic and foreign private returns to schooling δ0 and δ1 .4 Migration is a probabilistic event whose outcome is unknown when agents make their schooling choices, and an agent with s years of schooling who applies for migration has a probability p(s) ∈ [0, 1] to be admitted at destination. We assume that p(s) is differentiable and non-decreasing in s, thus allowing destination countries to adopt selective immigration policies which confer a better chance to migrate to applicants with a higher education. Agents have a logarithmic utility, so that the expected utility E [u(s)] of an agent with s years of schooling is given by E [u(s)] = [1 − p(s)] ln[(1 − τ0 )eω0 (s) e−c (s) ]
+ p(s) ln[(1 − τ0 )eω1 (s) e−c (s) ] = [1 − p(s)]ω0 (s) + p(s)ω1 (s) − c (s) + ln(1 − τ0 )
3 See Bertoli (2010) for a migration model where foreign wages are only locally observable, i.e. they cannot be observed before migration occurs. 4 The empirical literature has not yet reached a consensus on the relationship between the level of income of a country and the private returns to schooling: the extensive review by Psacharopoulos and Patrinos (2004) suggests that ‘‘the returns are lower in the high-income countries of the OECD’’, while Banerjee and Duflo (2005) argue that ‘‘the returns to one more year of education are [...] no higher in poor countries’’, and Barro and Lee (2010) recently provided evidence that the private rate of return to an additional year of schooling is higher in advanced countries than in lower-income countries. Furthermore, the literature suggests that relative migration costs decline with schooling (Chiquiar and Hanson, 2005; McKenzie and Rapoport, 2010), and it is the foreign return to schooling net of migration costs which drives schooling decisions at origin (Bertoli and Brücker, in press).
Given (1)–(4), the first order condition for the maximization of E [u(s)] is represented by5
δ0 + p(s)(δ1 − δ0 ) + p′ (s)[ω1 (s) − ω0 (s)] = 2γ0 (1 − σ0 )s.
(5)
The private return to schooling on the left-hand side of (5) is a weighted average of δ0 and δ1 , plus a nonnegative term that depends on the differential in log wages between the two countries, and on the extent to which the education–migration probability profile p(s) rewards an additional year of schooling in terms of better chances to migrate. For analytical convenience, we assume that p(s) is an affine function of schooling s p(s) = ϕ + κ s,
(6)
with due restrictions on ϕ and κ which ensure that p(s) ∈ [0, 1].6 Under the functional specification in (6), we can explicitly define the equilibrium level of schooling se0 (ϕ, κ) which maximizes E [u(s)], with se0 = s0 : se0 (ϕ, κ) =
δ0 + ϕ(δ1 − δ0 ) + κµ1 2 γ0 (1 − σ0 ) − κ δ1 − δ0 −
ξ0
.
(7)
2
2.1. Social welfare at origin We assume that social welfare is defined as the ex-post average utility of all domestic agents: this entails that the government is concerned also about the migrants, but we allow the weight assigned to migrants’ utility in the social welfare function to be lower than their actual share in the population at origin.7 Specifically, we define social welfare W (s, ϕ, κ) to be equal to W (s; ϕ, κ) = ap(s)ω1 (s) + [1 − ap(s)]ω0 (s) − γ0 s2 ,
(8)
where a ∈ [0, 1].8 The welfare-maximizing level of schooling s∗0 (ϕ, κ) is given by s∗0 (ϕ, κ) =
ξ0 + δ0 + aκµ1 + aϕ(δ1 − ξ0 − δ0 ) . 2[γ0 − aκ(δ1 − ξ0 − δ0 )]
(9)
The government can, through an adequate subsidy σ0 and budget-balancing taxes τ0 , ensure that s∗ (ϕ, κ) = se0 (ϕ, κ), but we abstract here from the decentralization of the first best. As we have ruled out heterogeneity across agents, s∗ (ϕ, κ) represents the level of education of both stayers and migrants. 2.2. The adoption of more selective immigration policies The welfare-maximizing level of schooling s∗0 (ϕ, κ) and the optimal-value function W ∗ (ϕ, κ) = maxs W (s; ϕ, κ) respond to variations in the parameters that characterize the probability to migrate p(s). What happens when the country of destination adopts more selective immigration policies? Such an analysis is conducted under the assumption, which is the same as in Stark and Wang (2002) and Docquier et al. (2008),9 that the interaction
5 Throughout the paper, we assume that (5) suffices to uniquely identify the optimal schooling choice. 6 Observe that (6) can be thought of as a linear approximation of a more general education–migration probability profile p(s). 7 A concern for the migrants could, for instance, be motivated by the fact that migrants transfer a portion of their foreign wages to the individuals left behind via remittances. 8 When a = 0, (8) coincides with the specification adopted in Stark and Wang (2002), where the government cares only about the individuals left behind, while when a = 1 the weight assigned to stayers’ and migrants’ utility coincide with the respective shares in the population. 9 Stark and Wang (2002) assume that migration policy is governed by the country of origin, but Stark (2004) argues that the analysis also applies to cases where ‘‘the enactment of migration policy is in the hands of the government of the destination country’’.
S. Bertoli, H. Brücker / Economics Letters 113 (2011) 19–22
between the governments in the two countries resembles a Stackelberg game: specifically, the government at destination behaves as the leader, while the government at origin acts as the follower, taking the immigration policy p(s) adopted at destination as given. This sort of interaction, as we demonstrate below, allows the country of destination to increase the selectivity of its immigration policy in such a way that keeps the scale of migration unchanged, and increases migrants’ education. 2.2.1. Selective immigration policies and migrants’ education The scale of migration is proportional to p(s); for any choice of κ , the country of destination can determine the value of ϕ which keeps the scale of migration unchanged at p¯ . This value of ϕ , ϕ(κ, p¯ ), is implicitly defined by the condition
ϕ(κ, p¯ ) = p¯ − κ s∗0 [ϕ(κ, p¯ ), κ],
(10)
where the government at destination makes full use of its knowledge of the reaction function of the country of origin. If we substitute (10) in (9), we get s∗0 (κ) =
ξ0 + δ0 + aκµ1 + ap¯ (δ1 − ξ0 − δ0 ) . 2γ0 − aκ(δ1 − ξ0 − δ0 )
(11)
Taking the partial derivative of (11) with respect to κ , we get
∂ s∗0 (κ) ∂κ =a
2γ0 µ1 + δ1 (ξ0 + δ0 ) − (ξ0 + δ0 )2 + p¯ (δ1 − ξ0 − δ0 )2
[2γ0 − aκ(δ1 − ξ0 − δ0 )]2
. (12)
If social welfare at origin is independent from migrants’ utility, i.e. a = 0 as in Stark and Wang (2002), then changes in immigration policies at destination are totally ineffective in influencing migrants’ education. If a ∈ (0, 1], as p¯ > 0, a sufficient condition for (12) to be positive is represented by 2γ0 µ1 + δ1 (ξ0 + δ0 ) − (ξ0 + δ0 )2 > 0, which, from (1), (4) and (9), is simply equivalent to
ω1 [s∗0 (ϕ, κ)]|ϕ,κ=0 > ω0 [s∗0 (ϕ, κ)]|ϕ,κ=0 .
(13)
This condition simply requires the wages at destination to be higher than the wages at origin when the level of schooling is equal to the first best when there are no options to migrate.10 Hence, whenever the government at origin cares also about the migrants, migrants’ education always increases with the adoption of a more selective immigration policy which keeps the scale of migration unchanged. 2.2.2. Selective immigration policies and welfare at origin How is social welfare at origin influenced by a shift toward a greater selectivity? The derivative of the optimal-value function W ∗ (ϕ, κ) with respect to κ under (10) can be expressed as
∂ W ∗ (ϕ, κ) ∂ s∗ (κ) = 2γ0 [s∗0 (κ)|κ=0 − s∗0 (κ)] 0 . (14) ∂κ ∂κ We already know that, when a = 0, (14) is equal to zero, and there is no variation in social welfare. If a ∈ (0, 1], then (14) is always negative, as s∗0 (κ) is monotonically increasing in κ . Hence,
a scale-preserving shift toward greater selectivity in immigration policies reduces social welfare at origin. 3. Discussion of the results and concluding remarks The analysis of the model in Section 2 suggests that there can be conflicting interests between the country of origin and
10 As s∗ (ϕ, κ)| ϕ,κ=0 also represents the welfare-maximizing level of schooling for 0 any pair (ϕ, κ) when the government only cares about the stayers, i.e. a = 0, (13) actually represents a necessary condition to observe migration flows from the origin to the destination country.
21
destination with respect to the setting of immigration policies, as more selective policies succeed in raising migrants’ education, but at the same time reduce welfare in migrant-sending countries. The model assumed that the government at origin can always decentralize the welfare-maximizing level of schooling, and it does not apply to the case considered in Docquier et al. (2008) where there are perception costs associated with levying taxes. If a more selective immigration policy increases the laissez-faire level of schooling chosen by domestic agents, then this could reduce the deadweight loss due to government intervention, and improve social welfare at origin via this channel. On the other hand, our results would be strengthened if we removed the assumption that the government is able to levy taxes on the migrants. The loss of fiscal revenues due to migration can be substantial (Desai et al., 2009), and it could strengthen the negative impact on welfare of more selective immigration policies. The analysis also assumed that the government at destination is both willing and able to opt for a greater selectivity in education while keeping the scale of migration unchanged. This assumption allowed us to develop the key contribution of this paper, which is represented by the focus on selectivity rather than openness of immigration policies, and it is consistent with the political stance toward migration that currently prevails in most destination countries. Nevertheless, it is easy to show that a change in immigration policy that combines both a greater selectivity and a greater openness11 can increase migrants’ education while improving social welfare at origin. Besides political willingness, such an outcome could also arise because of the inability of the government at destination to out-select prospective migrants while restricting options for non-selective immigration. Indeed, Beine et al. (2011) observe that ‘‘more selective migration policies might fail [to increase migrants’ education] unless family reunification programs are deeply reformed and limited’’. This paper shows that selective immigration policies can be an effective tool for increasing migrants’ education, and that the effects of a greater selectivity upon stayers’ education and social welfare at origin can diverge. The interests of the sending and recipient countries with respect to the design of immigration policies can conflict when a stronger out-selection in education is not matched by an increase in the scale of migration. References Banerjee, A V, Duflo, E., 2005. Growth Theory Through the Lens of Development Economics. In: Aghion, P., Durlauf, S.N. (Eds.), Handbook of Economic Growth, vol. 1A. Elsevier. Barro, R.J., Lee, J -W, 2010. A new data set of educational attainment in the World, 1950–2010, NBER Working Paper No. 15902, Cambridge MA. Beine, M., Docquier, F., Rapoport, H., 2001. Brain drain and economic growth: theory and evidence. Journal of Development Economics 64, 275–289. Beine, M., Docquier, F., Özden, C., 2011. Diasporas. Journal of Development Economics 95 (1), 30–41. Bertoli, S., 2010. The informational structure of migration decision and migrants’ self-selection. Economics Letters 108 (1), 89–92. Bertoli, S., Brücker, H., 2011. Extending the case for a beneficial brain drain, Jahrbücher für Nationalökonomie und Statistik, vol. 231 (in press). Bhagwati, J., 1979. International migration of the highly skilled: economics, ethics and taxes. Third World Quarterly 1, 17–30. Chiquiar, D., Hanson, G.H., 2005. International migration, self-selection, and the distribution of wages: evidence from Mexico and the United States. Journal of Political Economy 113 (2), 239–281. Desai, M.A., Kapur, D., McHale, J., Rogers, K., 2009. The fiscal impact of high-skilled emigration: flows of Indians to the US. Journal of Development Economics 88 (1), 32–44. Docquier, F., Faye, O., Pestieau, P., 2008. Is migration a good substitute for education subsidies?. Journal of Development Economics 86, 263–276.
11 In terms of the model, this can correspond to a situation where an increase in κ is associated with a variation (not necessarily an increase) in ϕ which gives rise to a larger scale of migration.
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Justman, M., Thisse, J.-F., 1997. Implications of the mobility of skilled labor force for local public funding of higher education. Economics Letters 55, 409–412. McKenzie, D.J., Rapoport, H., 2010. Self-selection patterns in Mexico-US migration: the role of migration networks. The Review of Economics and Statistics 92 (4), 811–821. Mountford, A., 1997. Can a brain drain be good for growth in the source economy? Journal of Development Economics 53 (2), 287–303. Stark, O., 2004. Rethinking the brain drain. World Development 32 (1), 15–22. OECD: 2009. The Future of International Migration to OECD countries. Paris: OECD.
Psacharopoulos, G., Patrinos, H.A., 2004. Returns to investment in education: a further update. Education Economics 12 (2), 111–134. Stark, O., Helmenstein, C., Prskawetz, A., 1997. A brain gain with a brain drain. Economics Letters 86, 227–234. Stark, O., Helmenstein, C., Prskawetz, A., 1998. Human capital depletion, human capital formation, and migration: a blessing or a ‘‘curse’’? Economics Letters 60 (3), 363–367. Stark, O., Wang, Y., 2002. Inducing human capital formation: migration as a substitute for subsidies. Journal of Public Economics 86 (1), 29–46.
Contents lists available at SciVerse ScienceDirect
Economics Letters journal homepage: www.elsevier.com/locate/ecolet
Selective immigration policies, migrants’ education and welfare at origin✩ Simone Bertoli a,∗ , Herbert Brücker b a
Robert Schuman Centre for Advanced Studies, European University Institute, Via delle Fontanelle 19, I-50014, San Domenico di Fiesole, Italy
b
University of Bamberg, IAB and IZA, Germany
article
info
Article history: Received 9 August 2010 Received in revised form 20 May 2011 Accepted 24 May 2011 Available online 1 June 2011
abstract Destination countries are increasingly adopting selective immigration policies. These can effectively increase migrants’ average education even if one allows for endogenous schooling decisions and education policies at origin. Still, more selective immigration policies can reduce social welfare at origin. © 2011 Elsevier B.V. All rights reserved.
JEL classification: F22 J24 H52 015 Keywords: International migration Selective immigration policies Education policies Social welfare
1. Introduction This paper analyzes the impact of selective immigration policies on migrants’ education and on welfare in the sending country in a model where schooling decisions and education policies at origin are endogenously determined. More and more destination countries are moving toward the adoption of immigration policies which out-select applicants on the basis of human capital criteria.1 The effects of this policy shift depend upon how prospective migrants adjust their schooling choices, and upon the possible changes in public policies toward education at origin. Our analysis draws on the literature on the beneficial brain drain (Mountford, 1997; Stark et al., 1997, 1998; Beine et al., 2001), which is built upon the idea that would-be migrants’
✩ The authors are grateful to an anonymous referee for the comments provided on the paper, and they also thank Sascha Becker, Tito Boeri, Giovanni Facchini, Anna Maria Mayda, Giovanni Peri and to the participants to the fRDB XI European Conference, Pisa, May 2009, for their suggestions; the usual disclaimers apply. Financial support from the NORFACE research programme on Migration in Europe – Social, Economic, Cultural and Policy Dynamics – and from the EU ‘‘Transnational networks of migrants (TOM)’’ Research and Training network is gratefully acknowledged. ∗ Corresponding author. Tel.: +39 0554685873. E-mail address: [email protected] (S. Bertoli). 1 ‘‘Countries that are non-selective and have relatively few highly skilled
immigrats [. . .] may be most likely to demand increased levels of highly skilled migration in the future’’ (OECD, 2009). 0165-1765/$ – see front matter © 2011 Elsevier B.V. All rights reserved. doi:10.1016/j.econlet.2011.05.036
schooling choices respond to the prospect to migrate. In his seminal contribution to this literature, Mountford (1997) argues that selectivity can improve the private incentives to invest in education, as would-be migrants want ‘‘to be eligible for emigration’’. This represents only a part of the story, as policy makers in origin countries do not behave as passive by-standers in the contest for talent, but rather adjust their education policies in response to changes in immigration policies. Such a reaction is induced by the fact that the policy stance at destination can affect the social return to education, as well as the private incentives to bear a larger share of its cost. The model that we propose is related to other papers that analyze the effects of a greater labor mobility on the financing of education (Justman and Thisse, 1997) and on migrants’ average education (Stark and Wang, 2002; Docquier et al., 2008). In contrast to the theoretical models by Stark and Wang (2002) and Docquier et al. (2008), which assume that destination countries adopt general immigration policies that do not outselect applicants with respect to their observable characteristics, our model considers not only the effects of a greater openness but also the effects of a greater selectivity, which is becoming an increasingly salient feature of immigration policies.2
2 In an extension of the model, Stark and Wang (2002) also consider immigration policies that are selective in education, but in a way that does not allow for separately analyzing the effects of selectivity.
20
S. Bertoli, H. Brücker / Economics Letters 113 (2011) 19–22
Our theoretical analysis reveals that a shift toward a more selective immigration policy which keeps the scale of migration unchanged improves the average level of schooling of the immigrants, and of the stayers at origin. While such a policy shift is beneficial for the countries of destination, it can be detrimental for the sending countries, where social welfare could fall. 2. Selective immigration policies and schooling choices We consider a small open economy populated by oneperiod lived agents. We assume perfect credit markets, and no heterogeneity across agents as in Stark and Wang (2002) and Docquier et al. (2008). An agent with s years of schooling earns a wage w0 (s) which is given by
w0 (s) = eω0 (s) = eµ0 +δ0 s .
(1)
We assume that education gives rise to positive externalities, so that the parameter µ0 in (1) is an increasing function of the average level of schooling in country 0, s0 . For the sake of simplicity, we assume a linear relationship between µ0 that and s0
µ0 = ξ0 s0 .
(2)
The time-equivalent cost of acquiring s years of schooling is given by 1 − e−c (s) = 1 − e−γ0 (1−σ0 )s , 2
(3)
where γ0 is a cost-shifter parameter and σ0 is a public education subsidy. The subsidy σ0 is financed with income taxes levied at a rate τ0 on all agents. This entails that the government is able to impose a Bhagwati-tax (Bhagwati, 1979) on migrants, and migration does not give rise to any fiscal loss. The value of τ0 is determined so to keep the fiscal budget balanced. Agents can apply for migration to a foreign country,3 where wages w1 (s) follow
w1 (s) = eω1 (s) = eµ1 +δ1 s .
(4)
We assume that µ1 > µ0 , while we do not introduce any assumption on the domestic and foreign private returns to schooling δ0 and δ1 .4 Migration is a probabilistic event whose outcome is unknown when agents make their schooling choices, and an agent with s years of schooling who applies for migration has a probability p(s) ∈ [0, 1] to be admitted at destination. We assume that p(s) is differentiable and non-decreasing in s, thus allowing destination countries to adopt selective immigration policies which confer a better chance to migrate to applicants with a higher education. Agents have a logarithmic utility, so that the expected utility E [u(s)] of an agent with s years of schooling is given by E [u(s)] = [1 − p(s)] ln[(1 − τ0 )eω0 (s) e−c (s) ]
+ p(s) ln[(1 − τ0 )eω1 (s) e−c (s) ] = [1 − p(s)]ω0 (s) + p(s)ω1 (s) − c (s) + ln(1 − τ0 )
3 See Bertoli (2010) for a migration model where foreign wages are only locally observable, i.e. they cannot be observed before migration occurs. 4 The empirical literature has not yet reached a consensus on the relationship between the level of income of a country and the private returns to schooling: the extensive review by Psacharopoulos and Patrinos (2004) suggests that ‘‘the returns are lower in the high-income countries of the OECD’’, while Banerjee and Duflo (2005) argue that ‘‘the returns to one more year of education are [...] no higher in poor countries’’, and Barro and Lee (2010) recently provided evidence that the private rate of return to an additional year of schooling is higher in advanced countries than in lower-income countries. Furthermore, the literature suggests that relative migration costs decline with schooling (Chiquiar and Hanson, 2005; McKenzie and Rapoport, 2010), and it is the foreign return to schooling net of migration costs which drives schooling decisions at origin (Bertoli and Brücker, in press).
Given (1)–(4), the first order condition for the maximization of E [u(s)] is represented by5
δ0 + p(s)(δ1 − δ0 ) + p′ (s)[ω1 (s) − ω0 (s)] = 2γ0 (1 − σ0 )s.
(5)
The private return to schooling on the left-hand side of (5) is a weighted average of δ0 and δ1 , plus a nonnegative term that depends on the differential in log wages between the two countries, and on the extent to which the education–migration probability profile p(s) rewards an additional year of schooling in terms of better chances to migrate. For analytical convenience, we assume that p(s) is an affine function of schooling s p(s) = ϕ + κ s,
(6)
with due restrictions on ϕ and κ which ensure that p(s) ∈ [0, 1].6 Under the functional specification in (6), we can explicitly define the equilibrium level of schooling se0 (ϕ, κ) which maximizes E [u(s)], with se0 = s0 : se0 (ϕ, κ) =
δ0 + ϕ(δ1 − δ0 ) + κµ1 2 γ0 (1 − σ0 ) − κ δ1 − δ0 −
ξ0
.
(7)
2
2.1. Social welfare at origin We assume that social welfare is defined as the ex-post average utility of all domestic agents: this entails that the government is concerned also about the migrants, but we allow the weight assigned to migrants’ utility in the social welfare function to be lower than their actual share in the population at origin.7 Specifically, we define social welfare W (s, ϕ, κ) to be equal to W (s; ϕ, κ) = ap(s)ω1 (s) + [1 − ap(s)]ω0 (s) − γ0 s2 ,
(8)
where a ∈ [0, 1].8 The welfare-maximizing level of schooling s∗0 (ϕ, κ) is given by s∗0 (ϕ, κ) =
ξ0 + δ0 + aκµ1 + aϕ(δ1 − ξ0 − δ0 ) . 2[γ0 − aκ(δ1 − ξ0 − δ0 )]
(9)
The government can, through an adequate subsidy σ0 and budget-balancing taxes τ0 , ensure that s∗ (ϕ, κ) = se0 (ϕ, κ), but we abstract here from the decentralization of the first best. As we have ruled out heterogeneity across agents, s∗ (ϕ, κ) represents the level of education of both stayers and migrants. 2.2. The adoption of more selective immigration policies The welfare-maximizing level of schooling s∗0 (ϕ, κ) and the optimal-value function W ∗ (ϕ, κ) = maxs W (s; ϕ, κ) respond to variations in the parameters that characterize the probability to migrate p(s). What happens when the country of destination adopts more selective immigration policies? Such an analysis is conducted under the assumption, which is the same as in Stark and Wang (2002) and Docquier et al. (2008),9 that the interaction
5 Throughout the paper, we assume that (5) suffices to uniquely identify the optimal schooling choice. 6 Observe that (6) can be thought of as a linear approximation of a more general education–migration probability profile p(s). 7 A concern for the migrants could, for instance, be motivated by the fact that migrants transfer a portion of their foreign wages to the individuals left behind via remittances. 8 When a = 0, (8) coincides with the specification adopted in Stark and Wang (2002), where the government cares only about the individuals left behind, while when a = 1 the weight assigned to stayers’ and migrants’ utility coincide with the respective shares in the population. 9 Stark and Wang (2002) assume that migration policy is governed by the country of origin, but Stark (2004) argues that the analysis also applies to cases where ‘‘the enactment of migration policy is in the hands of the government of the destination country’’.
S. Bertoli, H. Brücker / Economics Letters 113 (2011) 19–22
between the governments in the two countries resembles a Stackelberg game: specifically, the government at destination behaves as the leader, while the government at origin acts as the follower, taking the immigration policy p(s) adopted at destination as given. This sort of interaction, as we demonstrate below, allows the country of destination to increase the selectivity of its immigration policy in such a way that keeps the scale of migration unchanged, and increases migrants’ education. 2.2.1. Selective immigration policies and migrants’ education The scale of migration is proportional to p(s); for any choice of κ , the country of destination can determine the value of ϕ which keeps the scale of migration unchanged at p¯ . This value of ϕ , ϕ(κ, p¯ ), is implicitly defined by the condition
ϕ(κ, p¯ ) = p¯ − κ s∗0 [ϕ(κ, p¯ ), κ],
(10)
where the government at destination makes full use of its knowledge of the reaction function of the country of origin. If we substitute (10) in (9), we get s∗0 (κ) =
ξ0 + δ0 + aκµ1 + ap¯ (δ1 − ξ0 − δ0 ) . 2γ0 − aκ(δ1 − ξ0 − δ0 )
(11)
Taking the partial derivative of (11) with respect to κ , we get
∂ s∗0 (κ) ∂κ =a
2γ0 µ1 + δ1 (ξ0 + δ0 ) − (ξ0 + δ0 )2 + p¯ (δ1 − ξ0 − δ0 )2
[2γ0 − aκ(δ1 − ξ0 − δ0 )]2
. (12)
If social welfare at origin is independent from migrants’ utility, i.e. a = 0 as in Stark and Wang (2002), then changes in immigration policies at destination are totally ineffective in influencing migrants’ education. If a ∈ (0, 1], as p¯ > 0, a sufficient condition for (12) to be positive is represented by 2γ0 µ1 + δ1 (ξ0 + δ0 ) − (ξ0 + δ0 )2 > 0, which, from (1), (4) and (9), is simply equivalent to
ω1 [s∗0 (ϕ, κ)]|ϕ,κ=0 > ω0 [s∗0 (ϕ, κ)]|ϕ,κ=0 .
(13)
This condition simply requires the wages at destination to be higher than the wages at origin when the level of schooling is equal to the first best when there are no options to migrate.10 Hence, whenever the government at origin cares also about the migrants, migrants’ education always increases with the adoption of a more selective immigration policy which keeps the scale of migration unchanged. 2.2.2. Selective immigration policies and welfare at origin How is social welfare at origin influenced by a shift toward a greater selectivity? The derivative of the optimal-value function W ∗ (ϕ, κ) with respect to κ under (10) can be expressed as
∂ W ∗ (ϕ, κ) ∂ s∗ (κ) = 2γ0 [s∗0 (κ)|κ=0 − s∗0 (κ)] 0 . (14) ∂κ ∂κ We already know that, when a = 0, (14) is equal to zero, and there is no variation in social welfare. If a ∈ (0, 1], then (14) is always negative, as s∗0 (κ) is monotonically increasing in κ . Hence,
a scale-preserving shift toward greater selectivity in immigration policies reduces social welfare at origin. 3. Discussion of the results and concluding remarks The analysis of the model in Section 2 suggests that there can be conflicting interests between the country of origin and
10 As s∗ (ϕ, κ)| ϕ,κ=0 also represents the welfare-maximizing level of schooling for 0 any pair (ϕ, κ) when the government only cares about the stayers, i.e. a = 0, (13) actually represents a necessary condition to observe migration flows from the origin to the destination country.
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destination with respect to the setting of immigration policies, as more selective policies succeed in raising migrants’ education, but at the same time reduce welfare in migrant-sending countries. The model assumed that the government at origin can always decentralize the welfare-maximizing level of schooling, and it does not apply to the case considered in Docquier et al. (2008) where there are perception costs associated with levying taxes. If a more selective immigration policy increases the laissez-faire level of schooling chosen by domestic agents, then this could reduce the deadweight loss due to government intervention, and improve social welfare at origin via this channel. On the other hand, our results would be strengthened if we removed the assumption that the government is able to levy taxes on the migrants. The loss of fiscal revenues due to migration can be substantial (Desai et al., 2009), and it could strengthen the negative impact on welfare of more selective immigration policies. The analysis also assumed that the government at destination is both willing and able to opt for a greater selectivity in education while keeping the scale of migration unchanged. This assumption allowed us to develop the key contribution of this paper, which is represented by the focus on selectivity rather than openness of immigration policies, and it is consistent with the political stance toward migration that currently prevails in most destination countries. Nevertheless, it is easy to show that a change in immigration policy that combines both a greater selectivity and a greater openness11 can increase migrants’ education while improving social welfare at origin. Besides political willingness, such an outcome could also arise because of the inability of the government at destination to out-select prospective migrants while restricting options for non-selective immigration. Indeed, Beine et al. (2011) observe that ‘‘more selective migration policies might fail [to increase migrants’ education] unless family reunification programs are deeply reformed and limited’’. This paper shows that selective immigration policies can be an effective tool for increasing migrants’ education, and that the effects of a greater selectivity upon stayers’ education and social welfare at origin can diverge. The interests of the sending and recipient countries with respect to the design of immigration policies can conflict when a stronger out-selection in education is not matched by an increase in the scale of migration. References Banerjee, A V, Duflo, E., 2005. Growth Theory Through the Lens of Development Economics. In: Aghion, P., Durlauf, S.N. (Eds.), Handbook of Economic Growth, vol. 1A. Elsevier. Barro, R.J., Lee, J -W, 2010. A new data set of educational attainment in the World, 1950–2010, NBER Working Paper No. 15902, Cambridge MA. Beine, M., Docquier, F., Rapoport, H., 2001. Brain drain and economic growth: theory and evidence. Journal of Development Economics 64, 275–289. Beine, M., Docquier, F., Özden, C., 2011. Diasporas. Journal of Development Economics 95 (1), 30–41. Bertoli, S., 2010. The informational structure of migration decision and migrants’ self-selection. Economics Letters 108 (1), 89–92. Bertoli, S., Brücker, H., 2011. Extending the case for a beneficial brain drain, Jahrbücher für Nationalökonomie und Statistik, vol. 231 (in press). Bhagwati, J., 1979. International migration of the highly skilled: economics, ethics and taxes. Third World Quarterly 1, 17–30. Chiquiar, D., Hanson, G.H., 2005. International migration, self-selection, and the distribution of wages: evidence from Mexico and the United States. Journal of Political Economy 113 (2), 239–281. Desai, M.A., Kapur, D., McHale, J., Rogers, K., 2009. The fiscal impact of high-skilled emigration: flows of Indians to the US. Journal of Development Economics 88 (1), 32–44. Docquier, F., Faye, O., Pestieau, P., 2008. Is migration a good substitute for education subsidies?. Journal of Development Economics 86, 263–276.
11 In terms of the model, this can correspond to a situation where an increase in κ is associated with a variation (not necessarily an increase) in ϕ which gives rise to a larger scale of migration.
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