Demographic Research (May 2015)
Reconstructing trends in international migration with three questions in household surveys: Lessons from the MAFE project
Abstract
Background: Data on migration trends are crucially lacking in developing countries. The lack of basic information on migration contrasts sharply with the increasing importance of migration in the policy agenda of both sending and receiving countries. Objective: The general objectives of this paper are: to show how trends in international migration can be reconstructed with three questions in a household survey; to evaluate the precision of the estimates; and to test how sensitive the estimates are to several methodological choices and assumptions. Methods: Migration trends are reconstructed with event history models. The reconstruction uses data collected through migration surveys conducted in cities in three countries (Senegal, Democratic Republic of Congo, and Ghana) as part of the MAFE (Migration between Africa and Europe) project. Specifically, two types of data are used: simple data on the first migration of children of household heads, collected through household surveys, and full migration histories of children collected in biographic surveys. First, we evaluate the precision of our estimates using data collected in the household questionnaire. Next, the sensitivity of our results to different methodological choices and assumptions is evaluated. Results: Migration trends measured with simple data from household surveys are broadly consistent with results obtained from full migration histories. However, increases in migration trends tend to be underestimated with household data. Migration probabilities are also affected by large confidence intervals. Conclusions: Estimates using household data may be affected by large confidence intervals, and migrations trends are influenced by the simplifying assumptions that are made when using these data. Despite these limitations, estimates based on three simple questions provide useful information on migration levels and trends.