UNECE Task Force on the analysis of international migration estimates using different length of stay definitions Progress report UNECE/Eurostat Work Session on Migration Statistics Geneva, April 2010

Overview 1.Objectives of the Task Force 2.Data & metadata collected 3.Comparative analysis 4.Discussion of results 5.Conclusion and discussion

Issues raised at previous meetings Countries have different residency rules Definitions and availability of data on short-term migration Impact on comparability of international migration estimates

The definition problem Inconsistencies in definitions used across UNECE region Recent increase in short-term migration What is the impact of the use of different definitions on the estimation of international migration flows ? UN recommended definition: Long-term migrant = person who changes his/her country of usual residence for more than 12 months

Task Force United Kingdom – Jonathan Smith (chair) Austria – Stephan Marik-Lebeck Netherlands – Han Nicolaas Norway – Kare Vassenden Slovenia – Janja Povhe Switzerland – Marcel Heiniger

COUNTRYSOURCELENGTH OF STAY AustriaPopulation RegisterActual NetherlandsPopulation RegisterExpected SloveniaForeigner RegisterExpected Switzerland Central Migration Information System Expected for immigration Actual for emigration United Kingdom International Passenger Survey Actual for short-term Expected for long-term

Defining Migration Broader definition covers more moves larger migration estimates Alternative definitions considered: a)> 1 month b)> 3 months c)> 6 months d)> 12 months

Key points Broader length of stay definition results in larger migration estimates in all countries England & Wales: largest difference between ‘longer than 1 month’ and ‘longer than 3 months’ Netherlands: very short-term migrants (staying for less than 4 months) are not registered

Key points England & Wales: largest proportion of very short-term moves (1-3 months) Netherlands, Austria, and Switzerland: largest proportion of long-term moves (longer than 12 months) Slovenia: different pattern – underestimation of long-term migration (data based on intentions to stay in the country)

Expected vs. actual length of stay Trade-off between timeliness and accuracy Time lag when interviewing individuals on departure or waiting until they have been resident for 12 months Sample port survey: not possible to collect information retrospectively on individuals who never depart Uncertainty may be particularly acute with short-term moves (less than 12 months)

AUSTRIANETHERLANDSSLOVENIASWITZERLANDUNITED KINGDOM Time period ImmigrationYES EmigrationYES NOYES Reason for visitNOYES (for non-Dutch immigrants only) YES GenderYES AgeYES Sector of employmentNO YES Asylum statusNO YESNO Country of last residenceYES NO YES CitizenshipYES NO Circular migration movesYES (with more than 90-day intervals) YES (depending on registration of each entry/exit) YESNO Country of birthYES NOOnly born in CH or born abroad NO Parents’ country of birthNOYESNO Marital statusNOYESNOYESNO Position in householdNOYESNO

Immigration vs. emigration Emigration is generally more difficult to estimate than immigration England & Wales: passengers are sampled on entry and departure Switzerland: underestimation of emigration due to non-deregistration on departure Netherlands: administrative corrections made

Conclusion Broader definitions of migration result in larger migration estimates Impact of using broader definitions varies across countries considered Common issues identified with collection methods used - relevant to all migration data but more acute with shorter moves

Aims of the Task Force 1.Assess impact on international migration estimates when using different length of stay thresholds 2.Assess how well different data sources can be used to measure migration using a range of definitions 3.Assess availability and accuracy of short- term migration data

Discussion Relevance of this study to other countries Further analysis: –emigration data and implications on net migration –additional information collected: reason for visit, age and sex) –year on year fluctuations Further investigation into data collection methods – implications for countries developing or refining their systems