UNFPA/UNECE/NIDI Training programme on international migration, Geneva, 24-28/01/2005 Design of Samples for International Migration Surveys: Methodological Considerations, Practical Constraints and Lessons Learned from a Multi-Country Study in Africa and Europe George Groenewold (NiDi) Reference: Bilsborrow, R.E., Hugo, G., Oberai, A.S., Zlotnik, H International Migration Statistics. International Labour Office. Geneva. Groenewold, G. and R. E. Bilsborrow, Design of Samples for International Migration Surveys: Methodological Considerations, Practical Constraints, and Lessons Learned from a Multi-Country Study in Africa and Europe. Paper presented at Population Association of America (PAA) 2004 Conference, 1-3 April. Boston.

Specialised Migration Surveys T o study determinants and consequences of migration Key issue: data needed on appropriate comparison groups, i.e.: 1.Households in origin countries that have not migrated 2.Households in destination countries that migrated as entire households and come from the same origin country 3.Individual migrants in a destination country that come from the same origin country 4.Households remaining in the origin country from which someone emigrated to that destination country Implications for data collection -Examine countries that belong to same migration system ( Kritz and Zlotnik, 1992 ) -Undertake surveys in origin and destination countries -Use probability sampling

Sample design constraints Lack of sampling frames Households with international migration experience tend to concentrate in particular areas Migrants and their households tend to be ‘rare’ elements Presence of undocumented or illegal immigrants Options Concentrate sampling in particular regions within countries Use a special sampling strategy that ensures that sufficient numbers of ‘rare’ elements are selected and interviewed

Model sampling strategy 1.Purposively choose study regions in the country 2.Within each region, determine prevalence of migrant households in areas that constitute a region 3.Create ‘prevalence rate’ strata in each region and classify areas 4.Select areas each 'prevalence rate' stratum, over-sample areas in high prevalence rate strata 5.Screen migration status of all households in each selected area, create a migrant-household stratum and non-migrant household stratum, and classify households 6. Select migrant and non-migrant households, over-sample households in migrant-household stratum Characterisation Sampling of areas and households in multiple stages Over-sampling of high prevalence areas and migrant households Two phase sampling in last stage Derivation of sample design weights, to be used in analyses

Common features Intention of country-teams to develop probability samples Use of existing qualitative and quantitative information to determine prevalence of migrant households in areas Sampling of areas in multiple stages whereby areas with high prevalence of migrant households were over-sampled Two-phase sampling in the last stage: (1) screening of all households in sampled areas; (2) sampling and interviewing of households Differences Level of statistical representativeness aimed at: -Origin countries: Regional level -Destination countries: National level

Evaluation of over-sampling strategy: Egypt, Turkey and Morocco

Conclusions In most origin countries, sampling objective was realised such that about half of the target sample consists of the rare elements of interest (i.e. recent migrant households) In some countries the objective to generate statistically representative data was only partially met met due to certain implementation problems Differences between countries regarding the size of ‘regions’ for which data are actually statistically representative Sample selection bias: - whole households that migrated not covered in origin countries - return migrants and migrants who died not covered in destination countries

Recommendations Secure and allocate sufficient funds for: -Design of a proper and common sample design strategy -Monitor and document the implementation of the sample as the validity and precision of research findings depend on it In multi-country projects, a pre-project workshop on sampling design and implementation must be included, to discuss a model sampling strategy and ways to adapt it to local conditions, and identify potential sample implementation problems and ways to deal with them