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Monitoring international migration flows in Europe Frans Willekens

Explore a comprehensive analysis on enhancing European migration statistics for informed decision-making, covering issues such as underreporting, data accuracy, and measurement methods. Delve into statistical models and counting processes to estimate true migration flows accurately.

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Monitoring international migration flows in Europe Frans Willekens

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  1. Monitoring international migration flows in EuropeFrans Willekens Conference of European Statistics Stakeholders (CESS) Budapest, 21 October 2016. Session B8 – Migration: Data and Management

  2. Our society cannot function without reliable statistics(Marianne Thyssen, 20 October 2016) Statistics are indispensable for evidence-based decision making

  3. Improve migration statistics • A long journey and ongoing • Issues: • Definition of migration • Usual residence • Duration threshold • Coverage • Underreporting / undercount • Accuracy of data collection • Milestone • EU Regulation 682/2007 • Measurement and estimation

  4. Solution: synthetic data • Census • Survey • Administrative data Data (Measurements) Synthetic data (Estimates) Model • Other relevant information • quantitative • qualitative Distinguish between observations (data) and ’true’ migration flows

  5. Model of migration • Data generating process: counting process • Count data: number of migrations • Stochastic process {N(t), t ≥ 0}, with N(t) the ’true’ migration flows • Simplest counting process: Poisson process • One parameter, but varies by migrant category • Unobserved heterogeneity: mover-stayer model • Direction of migration: Origin - destination E(N) = λ var(N) = λ λ = 𝜇t

  6. Model of migration • How to estimate model from data? • Theory of counting processes • Number of migrations (occurrences) by origin, destination, and attributes of migrants and stayers • Exposure: • Number of persons exposed • Duration of exposure • Parameter of model: migration rate • Data are realisations of (underlying) counting process, e.g. Poisson process

  7. Model of migration • Use all relevant info: data and prior info • Types of prior information • Quantitative: primary data and auxiliary data • Qualitative: expert opinions • How to addprior information? • Information as probability distributions • Bayesianrule Prior

  8. Model of migration gamma distribution with shape parameter c=n+1 and scale parameter b=1/2 E(λ)=bc = (n+1)/2

  9. Observed vs ‘true’ migrations • Migration model predicts ‘true’ number of migrations • Measurement model quantifies difference between observed flows and ‘true’ flows (separate for origin and destination country) True flow = Observed flow * Correction factor

  10. How to obtain prior distribution?Expert opinion or model?Example: duration criterion • UN: permanent migrant stays at least 12 months • Poisson model with duration criterion

  11. How to obtain prior distribution?Expert opinion or model?Example: duration criterion

  12. How to obtain prior distribution?Expert opinion or model?Example: duration criterion • Mixture model (mover-stayer model) 𝜇 = 0.94 * 0.01 + 0.06 * 1.8

  13. Conclusion • Combine data from different sources • Meta data are essential • Use statistical models: • Migration model • Measurement model • Extend duration criterion to include short-term migration and circular migration • NSI should exchange migration data • Estimate emigration • Gain insight in drivers / root causes of migration: World Migration Survey

  14. Thank you

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