Emerging Issues in Migration Policies: Implications for Data Requirements

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Emerging Issues in Migration Policies:
Implications for Data Requirements
Bela Hovy, Chief
Migration Section
Population Division
Department for Economic and Social Affairs
United Nations, New York
http://www.unmigration.org
http://www.unpopulation.org
Presentation overview
1.
2.
3.
4.
Policy framework
Emerging issues and implications
for data collection
Examples
Conclusions
Resolution on International
Migration and Development
Commission on Population and Development, April 2006



Set up or strengthen institutions and mechanisms
for data collection and analysis to provide timely,
reliable and disaggregated migration data
Provide assistance to developing countries
Enhance cooperation between international
organizations in collection and processing of data
on migration and migrants
High-level Dialogue on
International Migration and Development
United Nations General Assembly, 14-15 September 2006

SG Report on International Migration and
Development (90 pages)
• Comprehensive overview
• Forum on Migration and Development

Other preparatory activities

Outcome:
• Migration policies based on sound evidence
• Enhanced availability, quality and timeliness of
migration data and information
Resolution on international
migration and development
General Assembly, 2nd committee, 1 December 2006




Development (MDGs) and human rights
dimensions
Global Forum on Migration and
Development, Belgium, 2007
Global Migration Group (GMG)
63rd session: options for HLD follow-up
Before “emerging issues”:
Three basic questions
1.
2.
3.
How many international migrants?
How many international migrant women,
children?
Where are the international migrants
coming from?
Transnational communities

From diaspora to transnational
communities (TNCs)

Economic and political interests

Definition and measurement issues
• Defining TNCs (stock)
• Defining national population
• Counting citizens or native born abroad
Return and circular migration

Potential for development (China, India)

Definition and measurement issues
• Definition of “return” (flow)
• Definition of “circulation” (flow)
• Measuring immigrating and emigrating
citizens
• Not just “short term” and “long term”
Migration of the highly skilled

Increase in demand and flows

“Brain drain”, compensation

Definition and measurement issues
• Tertiary education as proxy
• Global levels and trends unavailable
Irregular migration

Before arriving, upon entry, during stay

Concerns about protection, abuse, crime

Definition and measurement issues
•
•
•
•
Definition (irregular, undocumented, illegal)
Legal status: administrative data
No official data
Combining different data sources
Remittances


Most tangible contribution of international
migration to development
Definition and measurement issues
• New definition (IMF, WB, UNSD)
• Formal and informal flows
• Country of origin and destination (“remittance
corridors”)
Example 1. Migrant stock

Trends in total migrant stock: The 2005
revision (UNPD, 2006)
• Place of birth, citizenship, refugees
• Sex
• Coverage (DYB)

Age (migrant children, older migrants)
• Limited coverage
• Foreign citizens by age and sex not available
(DYB)

Country of birth or citizenship
• Not available (attempts)
Example 2. Migration flows

International migration flows: The 2005
Revision (UNPD, 2006)
• 15 countries, since 1960s
• Immigration, emigration, net migration
• Different criteria to define international
migrants:
 Place of residence
 Place of birth
 Citizenship

UNSD: not yet published
Conclusions (1) –
Data requirements

Increased pressure to deliver

Basic level
• trends and characteristics (sex, age, country of
birth/citizenship)

Complexity => distinctions
• Type of migrant (legal status, reason, duration
of stay, education/skills, vulnerable groups)
• Integration
• Impact
Conclusions (2) –
Sources


Improve tabulation and dissemination
(don’t wait for harmonization!)
2010 round of population censuses
• “Quantum leap or abject failure?”

Publish and use administrative data

Increased use of surveys

Combining data sources
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