The gain from the drain: skill-biased migration and global welfare
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Cites background from "The gain from the drain: skill-bias..."
...22 See Biavaschi et al. (2016) for a discussion on the population composition effects in the measurement of the skill selection of migrants (relative to non-migrants). higher education, which increases the proportion of tertiary educated after the liberalization (see the discussion in Sect....
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Cites methods from "The gain from the drain: skill-bias..."
...As for the nonagricultural sector, we use data on the wage ratio from Biavaschi et al. (2016) for 143 countries.28 We calibrate R$n using (3)....
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7 citations
Cites methods from "The gain from the drain: skill-bias..."
...Biavaschi et al. (2016) apply the same data to a different model and find an average welfare decrease of 1.8% at the world level and 3.5% for the OECD countries....
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References
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"The gain from the drain: skill-bias..." refers background or methods in this paper
...1 Own calculations from the 2010 OECD-DIOC database. Docquier & Rapoport (2012a) nd similar gures. 2 Mountford (1997), Stark et al. (1997), Vidal (1998) provide theoretical models showing how high-skilled emigration increases returns to education and triggers investment in human capital in the sending countries....
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...1 Own calculations from the 2010 OECD-DIOC database. Docquier & Rapoport (2012a) nd similar gures. 2 Mountford (1997), Stark et al....
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...1 Own calculations from the 2010 OECD-DIOC database. Docquier & Rapoport (2012a) nd similar gures....
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2,584 citations
2,141 citations
"The gain from the drain: skill-bias..." refers background or methods in this paper
...For the OECD countries, we compute these ratios from the "Education at a Glance" report 2010 (OECD, 2010)....
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...17 The share of output produced by foreign workers (ai ) is calibrated to match the educationspeci c wage premia for natives over immigrants, which is 5% in OECD countries. For nonOECD countries, we use the average value obtained in OECD countries (ai = 0.478) as we cannot assess country-speci c values due to the lack of immigration data. The production function includes three types of workers.18 To calibrate its structural parameters, we use parameter values obtained by Ottaviano & Peri (2012). To account for imperfect substitution between the three education groups, the elasticity of substitution, σs, is set to 5....
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...The 2010 DIOC database provides data on bilateral stocks by education level of migrants who went from 111 sending countries to the OECD and migrants who moved between all 34 OECD countries, as well as the population size and skill distribution of natives in the 34 OECD countries. The de nition of the three education levels is as follows: low-skilled individuals are those who achieved up to lower secondary or second stage of basic education; medium-skilled individuals obtained up to some post-secondary non-tertiary education; while high-skilled individuals have at least some tertiary education. To obtain the number and skill distribution of non-migrants for the nonOECD countries, we use data from Barro & Lee (2010).11 For the Rest of the World, we apply the average skill distribution of the available non-OECD countries....
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...The GDP per capita in Luxembourg the OECD's richest country is ve times larger than in Mexico, the OECD's poorest country. Moreover, in poorer countries the agricultural sector contributes a larger share to aggregate production. The productivity parameters Ai and A M i account for the di erences in aggregate productivity across as well as di erences in the sectoral productivity within countries. Second, as shown by Tre er (1993), countries considerably di er in their endowment of e ective labor. For instance, the same highskilled worker is more productive in the US than in Mexico, because in the US he/she faces a higher complementarity between capital and skill. We account for these di erences through country-speci c e ciency parameters for high- and low-skilled workers, αL i , α H i . Third, within a country, workers with similar skills are closer substitutes in production than workers with di erent skills (Card & Lemieux, 2001). We account for this imperfect substitutability by modeling the production function of the manufacturing sector with a CES structure. Fourth, as shown by Ottaviano & Peri (2012) and Peri & Sparber (2009), migrants and natives are imperfect substitutes even when they have the same level of education, which we account for in Equation (7) with an elasticity of substitution between immigrants and natives σn <∞ and country-speci c...
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...5 Both gures are based on the 2010 OECD-DIOC database. See Appendix E for the list of abbreviations. 6 These di erences in the skill compositions of migrants can be explained by supply and demand factors. On the supply side, they re ect individual self-selection in the migration decision, i.e. the degree to which immigration is an attractive option for tertiary-educated workers and the varying level of attractiveness of di erent destinations for di erent groups. On the demand side, receiving countries apply di erent degrees of skill-based migration policies, which determine the characteristics of the immigrant population. The canonical model of migrant self-selection is provided by Borjas (1987). For a discussion of the empirical evidence, see Biavaschi & Elsner (2013)....
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1,852 citations