Remittances and the Brain Drain
This trend is raising considerable concern among policymakers in developing countries, wary of having to bear the cost of educating and then losing their most entrepreneurial and talented workers. The possibility for educated migrants to move abroad should raise the returns to education and, in the end, may even lead to an increase in the number of educated workers who stay at home (Bhagwati and Hamada 1974; Bhagwati 1976; Mountford 1997; Stark, Helmenstein, and Prskawetz 1997, 1998). The European Community Household Panel is a closed panel and therefore cannot easily be used to study return migration. The key finding (table 1, column 3) is that more educated immigrants from non- EU countries are less likely to drop out of the panel, even after controlling for age, gender, employment status, and length of stay in the host country. The Pattern of Attrition in the European Community Household Panel Sample (dependent variable: probability that respondent does not drop out of the panel) Variable Household size Age Highest education Intermediate education Gender Employment Spouse Visitsa Minutesb Immigrant Immigrant EU Immigrant non-EU Lengthc ,5 years Lengthc 6 15 years Lengthc 16 25 years Constant Country dummy variable Time*origin Time dummy variable Number of observations Number of observations censored a Natives 0.012* Assume that the household is composed of two groups, one very close to the migrant and the other less close. Faini 185 Detragiache (1998) and Docquier and Marfouk (2004) relate the total number of skilled migrants to the Barro and Lee (2001) data set on educational achievements to derive a measure of migration rates for skilled workers, here defined as migrants having completed tertiary education. When the fact that 64 of 188 observations are censored at zero (using the Tobit maximum likelihood estimation procedure) is taken into account, the results are basically 8. In response to suggestions by a referee, a dummy variable for small island countries (mS/P) was introduced both additively and multiplicatively to capture the possibility that remittances are measured less accurately for these countries, which have the largest brain drain, thereby mechanically leading to a negative relation between (mS/P) and remittances. The findings of this article need to be confirmed by further research, especially at the household level.
| Main Author: | |
|---|---|
| Format: | Journal Article biblioteca |
| Published: |
World Bank
2007-05-30
|
| Subjects: | Brain Drain, developing countries, educated migrants, host country, immigration, immigration policies, Policy Research, Remittances, Skilled Migrants, skilled workers, |
| Online Access: | http://hdl.handle.net/10986/4453 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| id |
dig-okr-109864453 |
|---|---|
| record_format |
koha |
| spelling |
dig-okr-1098644532021-04-23T14:02:17Z Remittances and the Brain Drain Faini, Riccardo Brain Drain developing countries educated migrants host country immigration immigration policies Policy Research Remittances Skilled Migrants skilled workers This trend is raising considerable concern among policymakers in developing countries, wary of having to bear the cost of educating and then losing their most entrepreneurial and talented workers. The possibility for educated migrants to move abroad should raise the returns to education and, in the end, may even lead to an increase in the number of educated workers who stay at home (Bhagwati and Hamada 1974; Bhagwati 1976; Mountford 1997; Stark, Helmenstein, and Prskawetz 1997, 1998). The European Community Household Panel is a closed panel and therefore cannot easily be used to study return migration. The key finding (table 1, column 3) is that more educated immigrants from non- EU countries are less likely to drop out of the panel, even after controlling for age, gender, employment status, and length of stay in the host country. The Pattern of Attrition in the European Community Household Panel Sample (dependent variable: probability that respondent does not drop out of the panel) Variable Household size Age Highest education Intermediate education Gender Employment Spouse Visitsa Minutesb Immigrant Immigrant EU Immigrant non-EU Lengthc ,5 years Lengthc 6 15 years Lengthc 16 25 years Constant Country dummy variable Time*origin Time dummy variable Number of observations Number of observations censored a Natives 0.012* Assume that the household is composed of two groups, one very close to the migrant and the other less close. Faini 185 Detragiache (1998) and Docquier and Marfouk (2004) relate the total number of skilled migrants to the Barro and Lee (2001) data set on educational achievements to derive a measure of migration rates for skilled workers, here defined as migrants having completed tertiary education. When the fact that 64 of 188 observations are censored at zero (using the Tobit maximum likelihood estimation procedure) is taken into account, the results are basically 8. In response to suggestions by a referee, a dummy variable for small island countries (mS/P) was introduced both additively and multiplicatively to capture the possibility that remittances are measured less accurately for these countries, which have the largest brain drain, thereby mechanically leading to a negative relation between (mS/P) and remittances. The findings of this article need to be confirmed by further research, especially at the household level. 2012-03-30T07:12:35Z 2012-03-30T07:12:35Z 2007-05-30 Journal Article World Bank Economic Review 1564-698X http://hdl.handle.net/10986/4453 CC BY-NC-ND 3.0 IGO http://creativecommons.org/licenses/by-nc-nd/3.0/igo World Bank World Bank Journal Article Philippines Egypt, Arab Republic of Pakistan |
| institution |
Banco Mundial |
| collection |
DSpace |
| country |
Estados Unidos |
| countrycode |
US |
| component |
Bibliográfico |
| access |
En linea |
| databasecode |
dig-okr |
| tag |
biblioteca |
| region |
America del Norte |
| libraryname |
Biblioteca del Banco Mundial |
| topic |
Brain Drain developing countries educated migrants host country immigration immigration policies Policy Research Remittances Skilled Migrants skilled workers Brain Drain developing countries educated migrants host country immigration immigration policies Policy Research Remittances Skilled Migrants skilled workers |
| spellingShingle |
Brain Drain developing countries educated migrants host country immigration immigration policies Policy Research Remittances Skilled Migrants skilled workers Brain Drain developing countries educated migrants host country immigration immigration policies Policy Research Remittances Skilled Migrants skilled workers Faini, Riccardo Remittances and the Brain Drain |
| description |
This trend is raising considerable concern among policymakers in developing countries, wary of having to bear the cost of educating and then losing their most entrepreneurial and talented workers. The possibility for educated migrants to move abroad should raise the returns to education and, in the end, may even lead to an increase in the number of educated workers who stay at home (Bhagwati and Hamada 1974; Bhagwati 1976; Mountford 1997; Stark, Helmenstein, and Prskawetz 1997, 1998). The European Community Household Panel is a closed panel and therefore cannot easily be used to study return migration. The key finding (table 1, column 3) is that more educated immigrants from non- EU countries are less likely to drop out of the panel, even after controlling for age, gender, employment status, and length of stay in the host country. The Pattern of Attrition in the European Community Household Panel Sample (dependent variable: probability that respondent does not drop out of the panel) Variable Household size Age Highest education Intermediate education Gender Employment Spouse Visitsa Minutesb Immigrant Immigrant EU Immigrant non-EU Lengthc ,5 years Lengthc 6 15 years Lengthc 16 25 years Constant Country dummy variable Time*origin Time dummy variable Number of observations Number of observations censored a Natives 0.012* Assume that the household is composed of two groups, one very close to the migrant and the other less close. Faini 185 Detragiache (1998) and Docquier and Marfouk (2004) relate the total number of skilled migrants to the Barro and Lee (2001) data set on educational achievements to derive a measure of migration rates for skilled workers, here defined as migrants having completed tertiary education. When the fact that 64 of 188 observations are censored at zero (using the Tobit maximum likelihood estimation procedure) is taken into account, the results are basically 8. In response to suggestions by a referee, a dummy variable for small island countries (mS/P) was introduced both additively and multiplicatively to capture the possibility that remittances are measured less accurately for these countries, which have the largest brain drain, thereby mechanically leading to a negative relation between (mS/P) and remittances. The findings of this article need to be confirmed by further research, especially at the household level. |
| format |
Journal Article |
| topic_facet |
Brain Drain developing countries educated migrants host country immigration immigration policies Policy Research Remittances Skilled Migrants skilled workers |
| author |
Faini, Riccardo |
| author_facet |
Faini, Riccardo |
| author_sort |
Faini, Riccardo |
| title |
Remittances and the Brain Drain |
| title_short |
Remittances and the Brain Drain |
| title_full |
Remittances and the Brain Drain |
| title_fullStr |
Remittances and the Brain Drain |
| title_full_unstemmed |
Remittances and the Brain Drain |
| title_sort |
remittances and the brain drain |
| publisher |
World Bank |
| publishDate |
2007-05-30 |
| url |
http://hdl.handle.net/10986/4453 |
| work_keys_str_mv |
AT fainiriccardo remittancesandthebraindrain |
| _version_ |
1756571506210504704 |