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Richard E. Bilsborrow Consultant, MEDHIMS and World Bank

Comments on Papers in session on producing data on International Migration from surveys and other sources, and new experience with samples in egypt and jordan. Richard E. Bilsborrow Consultant, MEDHIMS and World Bank University of North Carolina at Chapel Hill Richard_bilsborrow@unc.edu

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Richard E. Bilsborrow Consultant, MEDHIMS and World Bank

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  1. Comments on Papers in session on producing data on International Migration from surveys and other sources, and new experience with samples in egypt and jordan Richard E. Bilsborrow Consultant, MEDHIMS and World Bank University of North Carolina at Chapel Hill Richard_bilsborrow@unc.edu Presented at ECE Work Session on Migration Statistics, Geneva, Switz. October 17-19, 2012

  2. Focus is on developing countries of net emigration • Data on individuals who have left (emigrated) from households can be obtained from household members remaining behind (proxy respondents) • Limitations in data that can be obtained from proxy respondents • In addition, data on whole households who emigrated is usually not available, and normally obtainable only through a survey in the country/ies of destination • This indicates a major limitation of a survey (or census) carried out only in a country of origin

  3. The existing state of knowledge on international migration • The state of knowledge is weak, partly due to the complexity of the phenomenon (including its definition, involving two countries, etc.) but also to the lack of good data sets and studies • To study the determinants and consequences of migration, survey data are needed on both individuals and households • This requires the use of specialized methods of data collection, including (1) sampling to address the “rare elements” problem and (2) questionnaires that collect retrospective data

  4. 1. Use of disproportionate sampling • In the country of Origin, goal is to sample (select) households with emigrants and those without emigrants (and possibly those with return migrants as well) • From the latest census or other source, form strata based on the expected prevalence of international migrants • Oversample areas or Primary Sampling Units (PSUs) from strata with higher proportions of households with emigrants at each sampling stage: This means selecting provinces or other PSUs at the first stage using oversampling, then at the second stage for selecting districts, etc., and finally in selecting the last stage area units (Ultimate Area Units or UAUs), such as census sectors or (urban) blocks. • Even highly disproportionate sampling fractions can be used, since that can be adjusted for in the analysis using weights.

  5. 2. Use two-phase sampling in last stage • Once the final Ultimate Area Units (UAUs) have been selected, in each sample UAU, first conduct a listing or screening operation, to list occupied households and identify those with and without migrants • Create separate lists for each type of household of interest, e.g., households with one or more former members who emigrated and did not return in the previous (e.g.) 10 years, those with someone who returned within the previous 10 years, and those without either—non-migrant households. • Sample from each list separately, taking high proportions from the lists of households with migrants and return migrants and small proportions of non-migrant households • In phase 2, conduct interviews of sample households from both lists

  6. Surveys to study the determinants and/or consequences of international migration • The key is to recognize the need to have data for appropriate comparison groups. I have written 2 books about this for the ILO (1984 and 1997). • Ideally, surveys should be conducted in both the country of origin and the main countries of destination. • If the survey can be carried out only in the country of origin (e.g., Jordan), it needs to cover households with emigrants (for whom data are obtained from proxy respondents) and households without emigrants. The appropriate comparison groups are (a) emigrants in the former; (b) persons who did not emigrate from both types of households. • To study why some persons emigrated and others did not, data on both (a) and (b) and their households (and communities) are pooled to estimate statistical migration functions. • To study the consequences of emigration, the same two groups are again compared. • To formulate policy recommendations, it is desirable to conduct studies on both the determinants and consequences.

  7. Now to the papers and what light they shed on the data collection problems • Thorogood, Jensen and Schachter on Suitland group contributions, on 3 of 7 projects begun following meeting in 2009 • Pie (not Psy!) • (Read brief comments on Thorogood & Jensen} • Re. Jason, provides interesting review of a number of hard-to-reach populations who move • Based on questionnaire to 29 Europ countries in 2008 • Upcoming conference of ASA

  8. More on Suitland….. • Some types of hard-to-reach involve issue of purpose of migand defn, discussed well, but of minor interest to me; see Standing’s Typology in 1984 book of Bilsborrow et al on internal migration—short term, circular, while others so difficult—trafficked, in transit • But is data on transit mig so hard to get in surveys? • Or forced migration? Samir and our MEDSTAT group including UNHCR (Tarek) developed nice screening question, and follow-up questionnaire • In Fig. 1 Jason adds minors; I started working on this for UNICEF in 2007, collapsed, but I think is ongoing? • Says it is “most likely unfeasible to implement surveys to collect data” on hard to reach pops, plus is too costly—but I think we can—or must try!

  9. MEDHIMS Surveys • To complement what Samir has said, we propose to use specialized sampling techniques appropriate for rare populations, where possible • In first country, there was not adequate frame to make it possible, so a PPES sample was used • But in Jordan, there seemed to be two sources which, while each is inadequate, proved feasible to use when considered together

  10. What to do if have 2 different, dubious sources of data? Example of new sample in Jordan for 2013

  11. Example of oversampling PSUs: Jordan, 2013

  12. So let us move forward, in both the MEDHIMS region and CIS States, and surprise the world!

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