A gendered assessment of the brain drain

This paper updates and extends the Docquier-Marfouk data set on inter-national migration by educational attainment. The authors use new sources, homogenize definitions of what a migrant is, and compute gender-disaggregated indicators of the brain drain. Emigration stocks and rates are provided by level of schooling and gender for 195 source countries in 1990 and 2000. The data set can be used to capture the recent trend in women's skilled migration and to analyze its causes and consequences for developing countries. The .findings show that women represent an increasing share of the OECD immigration stock and exhibit relatively higher rates of brain drain than men. The gender gap in skilled migration is strongly correlated with the gender gap in educational attainment at origin. Equating women's and men's access to education would probably reduce gender differences in the brain drain.

Type: 
Time Series
Topics: 
Economic Growth
Education
Financial Sector Development
Gender
Health, Nutrition and Population
Social Development
Economy Coverage: 
Blend
High Income
IBRD
IDA
Low Income
Lower Middle Income
Upper Middle Income
Languages Supported: 
English
Number of Economies: 
195
Geographical Coverage: 
World
East Asia & Pacific
American Samoa
Australia
Brunei Darussalam
Cambodia
China
Cook Islands
Fiji
French Polynesia
Guam
Hong Kong SAR, China
Indonesia
Japan
Kiribati
Korea, Dem. People's Rep.
Korea, Rep.
Lao PDR
Macao SAR, China
Malaysia
Marshall Islands
Micronesia, Fed. Sts.
Mongolia
Myanmar
Nauru
New Caledonia
New Zealand
Niue
Northern Mariana Islands
Palau
Papua New Guinea
Philippines
Samoa
Singapore
Solomon Islands
Taiwan, China
Thailand
Timor-Leste
Tonga
Tuvalu
Vanuatu
Vietnam
Europe & Central Asia
Albania
Andorra
Armenia
Austria
Azerbaijan
Belarus
Belgium
Bosnia and Herzegovina
Bulgaria
Channel Islands
Croatia
Cyprus
Czech Republic
Denmark
Estonia
Faroe Islands
Finland
France
Georgia
Germany
Gibraltar
Greece
Greenland
Hungary
Iceland
Ireland
Isle of Man
Italy
Kazakhstan
Kosovo
Kyrgyz Republic
Latvia
Liechtenstein
Lithuania
Luxembourg
Macedonia, FYR
Moldova
Monaco
Montenegro
Netherlands
Norway
Poland
Portugal
Romania
Russian Federation
San Marino
Serbia
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Tajikistan
Turkey
Turkmenistan
Ukraine
United Kingdom
Uzbekistan
Latin America & Caribbean
Anguilla
Antigua and Barbuda
Aruba
Argentina
Bahamas, The
Barbados
Belize
Bolivia
Brazil
British Virgin Islands
Cayman Islands
Chile
Costa Rica
Colombia
Cuba
Curaçao
Dominica
Dominican Republic
Ecuador
El Salvador
Grenada
Guatemala
Guyana
Haiti
Honduras
Jamaica
Martinique
Mexico
Montserrat
Netherlands Antilles
Nicaragua
Panama
Paraguay
Peru
Puerto Rico
Sint Maarten (Dutch part)
St. Barthélemy
St. Kitts and Nevis
St. Martin (French part)
St. Lucia
St. Vincent and the Grenadines
Suriname
Trinidad and Tobago
Turks and Caicos Islands
Uruguay
Venezuela, RB
Virgin Islands (U.S.)
Middle East & North Africa
Algeria
Bahrain
Egypt, Arab Rep.
Djibouti
Iraq
Iran, Islamic Rep.
Israel
Jordan
Kuwait
Lebanon
Libya
Malta
Morocco
Oman
Qatar
Saudi Arabia
Syrian Arab Republic
West Bank and Gaza
United Arab Emirates
Tunisia
Yemen, Rep.
North America
Bermuda
Canada
United States
South Asia
Afghanistan
Bangladesh
Bhutan
India
Pakistan
Nepal
Maldives
Sri Lanka
Sub-Saharan Africa
Angola
Benin
Botswana
Burkina Faso
Burundi
Cabo Verde
Cameroon
Central African Republic
Chad
Comoros
Congo, Dem. Rep.
Congo, Rep.
Côte d'Ivoire
Ethiopia
Eritrea
Equatorial Guinea
Gabon
Gambia, The
Ghana
Guinea
Guinea-Bissau
Kenya
Lesotho
Liberia
Madagascar
Malawi
Mali
Mauritania
Mauritius
Mozambique
Namibia
Niger
Nigeria
Reunion
Rwanda
São Tomé and Principe
Seychelles
Senegal
Sierra Leone
Somalia
South Africa
South Sudan
Sudan
Eswatini
Tanzania
Togo
Uganda
Zambia
Zimbabwe
Access Options:
Download
Temporal Coverage: 
1990 - 2000
Release Date: 
May 1, 2008

Last Updated

Last Updated: 
July 1, 2010
EXCEL ZIP

Data

Although women's mobility accounts for a large and increasing proportion of international migration, it has generally been overlooked in the literature. Quantifying and characterizing female migration is clearly a next step on the path to a better understanding of the forces that shape the international migration of people. In this paper, we build an original data set providing gender disaggregated indicators of international migration by educational attainment for 195 source countries in 1990 and 2000. The findings show that women represent an increasing share of the OECD immigration stock and exhibit relatively higher skilled emigration rates than men. The gender gap in high-skill migration is strongly correlated with the gender gap in educational attainment at origin.
Resource Type: Download Format: EXCEL ZIP

No Visualizations Available.

This paper updates and extends the Docquier-Marfouk data set on inter-national migration by educational attainment. The authors use new sources, homogenize definitions of what a migrant is, and compute gender-disaggregated indicators of the brain drain. Emigration stocks and rates are provided by level of schooling and gender for 195 source countries in 1990 and 2000. The data set can be used to capture the recent trend in women's skilled migration and to analyze its causes and consequences for developing countries. The .findings show that women represent an increasing share of the OECD immigration stock and exhibit relatively higher rates of brain drain than men. The gender gap in skilled migration is strongly correlated with the gender gap in educational attainment at origin. Equating women's and men's access to education would probably reduce gender differences in the brain drain.

Data Resources

Dataset Info

These fields are compatible with DCAT, an RDF vocabulary designed to facilitate interoperability between data catalogs published on the Web.
FieldValue
Groups audience
Modified Date
2018-09-14
Release Date
December 31,1969
Periodicity
Periodicity not specified
Identifier
ecb5bbd0-9f45-452e-b6a5-d48ad4ef1ad0
License
License Not Specified
Temporal Coverage
Temporal Coverage: 
1990 - 2000
Rating: 
0
No votes yet
Type: 
Languages Supported: 
Number of Economies: 
195
Geographical Coverage: 
Data Classification of a Dataset: 
Start Date: 
Monday, January 1, 1990
End Date: 
Sunday, December 31, 2000
DEC
Release Date: 
Thursday, May 1, 2008
Last Updated Date: 
Thursday, July 1, 2010
Granularity: 
Modified date: 
14790
Primary Dataset: 
Yes

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This dataset is licensed under CC-BY 4.0

CC-BY 4.0

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