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Enhancing Migration Data Collection Using Multi-Topic Household Surveys: Lessons from Albania

Explore Albania's experience in collecting migration data through surveys, addressing issues like lack of data sources, definitions, sampling, and household membership. Learn about modeling migration, tracking migrants, and the impact on policy.

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Enhancing Migration Data Collection Using Multi-Topic Household Surveys: Lessons from Albania

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  1. Collecting Migration Data using Multi-topic HH surveys: the Albania Experience Gero Carletto DECRG, The World Bank Jan 24, 2008

  2. The issues • Lack of data, haphazard efforts • Sources • PopCensus (immigration; internal, undercount; frequency) • Border crossings, admin records (undocumented?) • Surveys (representative?). Little attention … • Remittances (official only). • Definitions • Migrant • Permanent vs. temporary/seasonal/circular • Returnees • HH membership/headship

  3. The issues (cont’d) • Sampling • Rare event, clustered • Probability vs. non-probability sampling • Survey options • Stand-alone vs. piggybacked • Identification • Remittances

  4. Albania: the context • “Quasi-experimental” setting • 1990 • Huge outflows • International (permanent vs. temporary) • Internal • Geography • Piggyback approach (2002-05) • Gradual • Pilots and training

  5. ALSMS innovations • HH membership • Histories • Networks • Tracking migrants • Identification

  6. Household membership • Prototype LSMS definition • Fertility module (2002) • Underestimate if mother absent • “Relaxed” definition (2005) • Double counting? • Extended roster

  7. Migration histories • High mobility, internal and external • Both permanent and temporary • Permanent/long vs. shorter episodes (Smith and Thomas, 2003) • “Bound” grid for hh members • Clear time marks • Up to 3 episodes for non-hh members • Detailed characterization

  8. Migration histories

  9. Networks • Immediate family • Children and spouse • Time of migration (and return?) • Siblings of HH head and spouse • Destination, gender, occupation, … • Networks in 1990

  10. Modeling migration • Hazard model • Probability of migration in any given time period t, conditional on not having migrated up through time t-1 • Diffusion (time dimension) • Time-varying covariates

  11. Hazard model

  12. Tracking migrants • Contact info • Process • Greece only; list of migrants with contacts • 1st contact in Greece • Return visit in Fall (phone cards) • 2nd contact in Greece • Interview • High attrition • No contact info • Unable to locate • Refusal (not high) • Returnees/high mobility • Selection bias(es) [undocumented]

  13. Identification • Migration decision not random • Instruments: determinants of migration, not correlated with outcome of choice • “By being clever, it is often possible to come up with convincing instruments” (Woolridge) • Pre-1990 conditions • Languages • Propensity to move • Network • Distances

  14. Impact on policy • Determinants of migration (by gender) • Dynamic model • Impact of migration at origin on … • Welfare • Agriculture and livestock • Business ownership • Occupational choice • 2003 and 2007 PA • Long process. Dissemination?

  15. LSMSIV: next steps • HH membership/headship • Imputing total remittances • Better identification, matching • Tracking • Experimental design (?)

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