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Serial correlation in multiregional migration models.

D K Foot, W J Milne

    Journal of Regional Science
    |November 1, 1990
    PubMed
    Summary
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    This study on multiregional net migration highlights the importance of accounting for serial correlation in time-series models. Correcting for this statistical pattern significantly improves migration equation accuracy.

    Area of Science:

    • Demography
    • Econometrics
    • Regional Science

    Background:

    • Multiregional migration patterns are crucial for understanding population dynamics.
    • Traditional time-series models may not fully capture the complexities of migration flows.
    • Serial correlation in migration data can bias statistical estimates.

    Purpose of the Study:

    • To specify and estimate multiregional net-migration equations incorporating first-order serial correlation.
    • To investigate the impact of the nonstochastic adding-up constraint on serial-correlation coefficients.
    • To demonstrate the necessity of serial correlation correction in migration modeling.

    Main Methods:

    • Specification of multiregional net-migration equations.
    • Estimation of time-series models with serial correlation adjustments.
    Keywords:
    AmericasCanadaDemographic FactorsDeveloped CountriesMigrationMigration, InternalModels, TheoreticalNorth AmericaNorthern AmericaPopulationPopulation DynamicsResearch MethodologyTime Factors

    Related Experiment Videos

  • Application of the adding-up constraint to restrict serial-correlation parameters.
  • Empirical analysis using Canadian provincial data (1962-1985).

    • Main Results:

    • The adding-up constraint significantly restricts serial-correlation coefficients in multiregional migration systems.
    • Serial correlation coefficients were found to be statistically significant.
    • The inclusion of serial correlation correction improved the accuracy of migration estimates.

    Conclusions:

    • First-order serial correlation is a significant factor in multiregional net-migration time-series.
    • Ignoring serial correlation can lead to inaccurate migration modeling.
    • Future time-series analyses of multiregional migration should incorporate serial correlation corrections.