CARIM-East Methodological Workshop II Warsaw, 27-28 October 2011 Improving International Migration Statistics Selected examples from OECD Jean-Christophe Dumont Head of International Migration Division Directorate for Employment, Labour and Social Affairs OECD
Key challenges for international migration statistics Policy relevance Coverage / definition Comparability (time/country) Timeliness
Definition and policy relevance
International comparability - How can one compete with the richness and diversity of national data sources? -The complexity of international comparisons But Provide benchmarks for national performance Show features that are not visible by looking at national data alone Permit generalisations across countries Help to focus on the right questions
Selected examples from OECD I. Databases on Immigrants in OECD Countries (DIOC) II. Standardised international migration statistics III. Return migration and retention rates IV. Indicators of integration of immigrants
I. Databases on Immigrants in OECD Countries (DIOC) Why? Provide policy makers and public opinion with more internationally comparable migration statistics to help dispel some myths Shed new light on the so-called «brain drain» What? Data from 28 OECD population censuses and population registers, covering more than 200 origin countries circa 2000. Data were compiled on 15+ by country of birth, citizenship, education, age, gender, duration of stay, employment status, occupation, sector of activity and field of study A Profile of Immigrant Populations in the 21 st Century. Data from OECD Countries (OECD 2008) Data available on: www.oecd.org/els/migration/dioc
I. Databases on Immigrants in OECD Countries (DIOC) DIOC-E 2000 : 32 OECD countries and 68 non-oecd countries, population registers and census data o 120 million migrants aged 15 and over representing 75% of the estimated number of international migrants worldwide in 2000 o Key role of intraregional migration: Africa: 92% of the immigrants were born in Africa Asia: 66% Latin America: 62% Europe: 61% New possibilities to analyses regional migration patterns o 26 million highly skilled migrants (22%), of which only 6.9 million live in non-oecd countries Data available on: www.oecd.org/migration/dioc/extended
Highly skilled emigration rate I. Databases on Immigrants in OECD Countries (DIOC) Total emigration rate and emigration rate of highly educated by country of birth, population aged 15 and over, circa 2000 100% 90% BRB 80% 70% 60% HTI TTO MUS TON 50% KHM JAM MOZ 40% KEN COG SYC GHA FJI MLT PRI 30% BDI CUB ALB BEN PAN SLV NIC BHR FYUG-HRV 20% CYP IRL PRT 10% USSR-ARM USSR-KAZ MEX USSR-BLR 0% 0% 5% 10% 15% 20% 25% 30% 35% 40% 45% 50% BLZ Total emigration rate GUY
I. Databases on Immigrants in OECD Countries (DIOC) DIOC 2005/06 : 25 OECD countries, population registers, census data and labour force survey data o o o 91 m foreign-born live in the 25 OECD countries covered by DIOC 2005/06, of which 16.5 m are recent immigrants 10.8% of the total population in the OECD is foreign-born in 2005/06, compared to 9.5% in 2000 Despite increasing educational attainment levels in origin countries, emigration rates of the highly skilled increased Share of immigrants in OECD countries, population aged 15 and over, 2000 and 2005/06 45% 40% 35% 30% 25% 20% 15% 10% 5% 0% 100% 46% 2005/06 2000 % change in share 2000-2005/06
I. Databases on Immigrants in OECD Countries (DIOC) Characteristics of migrants from former USSR countries living in the OECD, population aged 15 and over, circa 2005/06 Foreign-born % women % young (aged 15-24) % higheducated Russian Federation 2,189,054 56 18 28 Ukraine 1,153,776 59 11 35 Former USSR 645,392 52 18 18 Belarus 176,901 61 9 34 Armenia 122,551 52 19 38 Moldova 87,261 56 19 37 Georgia 50,940 53 19 39 Azerbaijan 28,951 55 15 52
Participation rate in the OECD I. Databases on Immigrants in OECD Countries (DIOC) Participation rates of foreign-born women aged 15 and over in the OECD and in their country of origin, 2005/06 1.00 0.90 0.80 0.70 0.60 0.50 0.40 0.30 0.20 0.10 BGR HND NIC SEN IRN LKA EGY MAR DZA LBN TUN MLT IRQ TUR SYR PAK BGD ECU PER PHL CYP IDN AZE USSR-UKR GHA BHS MDG KHM 0.00 0.00 0.20 0.40 0.60 0.80 1.00 Participation rate in origin country TZA
I. Databases on Immigrants in OECD Countries (DIOC) What is missing & limitations : Data on stocks represent the cumulative effect of net migration flows over past decades Imperfect, heterogeneous and unknown coverage of certain categories of migrants : undocumented migrants, temporary migrants, asylum seekers Some persons with unknown country of birth and/or educational level Specific hypotheses for some countries (Japan, Germany) Problems for decomposed/recomposed countries of origin Distinction between foreign-educated and foreign-born who were educated in the destination country
II. Standardised international migration flows National official statistics are generally extracted from the population registers. Breakdown by age, sex, nationality but not by category of entry Data not comparable across countries, no possibility of adding up movements across countries Chart 1. Estimated retention rate (1992-2001) by intended stay criterion for entry into the population or foreigners' register (retention rate=net migration as a percentage of the inflows) 80 70 60 50 40 30 20 10 0 Germany - 7 days Switzerland - 1 year Japan - 90 days Belgium - 3 months Luxembourg - 4 months Netherlands - 4 months Norway - 6 months Sweden - 1 year Denmark - 1 year Finland - 1 year
II. Standardised international migration flows Immigration into OECD countries, 1985-2009 (1985=100) 800 700 600 Australia + Canada Germany 500 400 Japan 300 200 United States 100 0 1985 1990 1995 2000 2005 2009 EEA (excl. CHE+DEU)
II. Standardised international migration flows Permanent- vs temporary- based migration Ignored UN statistical recommendations Focused on regulated flows (+ free movement) Use residence permits and visas by category of entry instead of registers Disentangle permanent from temporary permits, based on what receiving countries consider are for the long term Disaggregate data by category (work, family, humanitarian + free movements)
II. Standardised international migration flows Country National vs OECD standardised statistics (2006) OECD standardised National Difference Difference (%) Japan 87 600 325 600-238 900-73 Germany 216 000 558 500-342 500-61 United Kingdom 343 200 451 700-108 500-24 Canada 251 600 251 600 0 0 United States 1 266 300 1 266 300 0 0 Italy 204 300 181 500 22 800 13 France 169 000 135 100 33 900 25 OECD (18 countries) 3 241 900 4 001 900-760 000-19
II. Standardised international migration flows Permanent-type immigration by main category as a % of the total population, 2008 2.0 1.8 Work Free movement Family and accompanying family of workers Humanitarian and other 1.6 1.4 1.2 1.0 0.8 0.6 0.4 0.2 0.0
II. Standardised international migration flows Steps forwards : Temporary labour migration: improve the coverage and focus on specific movements (Intra-corporate transfers, Cross-border service provision) Distinguish changes in status from cross border movements (ex: growing area: permanent-based migration of students) Breakdown data by gender, nationality, educational level
III. Return migration and retention rates Method for estimating returns using a census in the origin country
III. Return migration and retention rates Indirect estimation method of immigrants exits from the destination country
III. Return migration and retention rates Retention rates of immigrants after 3 and 5 years of residence for selected European countries, population aged 15 and older %
III. Return migration and retention rates Status changes (work, family, other) Stay rate = Students not renewing their student permits With: Students not renewing their student permits = (New Student permits delivered) n (#Student permits n+1 - #Student permits n )
IV. Indicators of integration of immigrants Comparing immigrants: with whom? Comparison between immigrant groups Comparison with a «reference» group Comparison over time Immigrants specific features (origin, language proficiencies, citizenship) Which «reference» group: several options (Total population; Non-immigrants; Non-immigrants with same characteristics) Data issues in measuring progress over time Calculation of differences in rates between the different groups Calculation of differences (observed and assuming same socio-demographic structure) Differences in % points or in % (growth rate)
20 30 40 50 60 70 80 90 100 HE RC ITA RT BR UX ZE OR VK CD LD UT UN NK IRL EU WE FIN SP RA EL IV. Indicators of integration of immigrants Employment rates of the foreign-born men (15-64) (%) Percentage points differences vs natives Foreign-born less likely to be employed Observed Adjusted Foreign-born more likely to be employed CHE GRC ITA PRT GBR LUX CZE NOR SVK OECD NLD AUT HUN DNK IRL DEU SWE FIN ESP FRA BEL
IV. Indicators of integration of immigrants
IV. Indicators of integration of immigrants Differences with the native-born populations (% points) Change in employment rates of the foreign-born population, 2000-01 to 2008-09 10 5 Men and women GRC ITA ESP LUX IRL PRT Immigrants are more likely to be employed than the native-born population 0-5 FRA AUT CHE Immigrants are less likely to be employed than the native-born population -10 DEU GBR NOR -15 DNK BEL FIN NLD SWE 45 50 55 60 65 70 75 80 Employment rates of the foreign-born Source: EU Labour Force Survey database.
IV. Indicators of integration of immigrants INDICATORS by DOMAIN Immigrants outcomes and progress Material living conditions Health Labour market Social integration Household income Housing/local environment Health status Access to health care Employment Unemployment Features of the current job Participation to national elections Trust in institutions Discriminations Offspring of immigrants Outcomes and progress CONTEXTUAL INDICATORS 1. Size, age and gender composition of the foreign-born population 2. Composition of the foreign-born population by gender and duration of stay 3. Origin country 4. Educational attainment 5. Origin of diploma 6. Nationality of the foreign-born population 7. Language skills 8. Reason for migration 9. Degree of urbanisation 10. Size and composition of households Material living conditions Children living in poverty 1. Size and age composition of the Education Labour market Social integration Participation in childcare (2-6 yrs old) PISA results of children of immigrants Drop out Same as above + NEET Same as above population of offspring of immigrants 2. Children by type of household 3. Concentration in schools Contextual information on the host country Average number of years to get naturalised Place of diploma and proportion who got their qualifications recognised Public opinion on immigration
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