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Sensitivity analysis of discrete-time interregional population systems

K L Liaw

    Demography
    |November 1, 1976
    PubMed
    Summary

    This study analyzes how population growth and distribution are impacted by changes in regional birth rates and migration. The findings offer insights into population dynamics and sensitivity analysis for demographic models.

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    Area of Science:

    • Demography
    • Mathematical Modeling
    • Population Dynamics

    Background:

    • Interregional population systems are complex, influenced by natural growth and migration.
    • Understanding the sensitivity of these systems to demographic changes is crucial for policy and planning.
    • Previous models often lack detailed sensitivity analysis for both growth rate and distribution.

    Purpose of the Study:

    • To analytically investigate the impact of small changes in regional growth rates and migration on long-run population dynamics.
    • To apply these analytical methods to a specific case study (Canadian population system).
    • To demonstrate the applicability of the method for sensitivity analysis in demographic models like the Leslie model.

    Main Methods:

    • Analytical derivation of sensitivity measures for population growth and distribution.
    • Utilizing a time-homogeneous structural matrix for the interregional population system.
    • Application of the derived methods to an empirical eight-region Canadian population dataset.

    Main Results:

    • Quantified the effects of variations in natural growth rates on the long-run population growth rate.
    • Determined the influence of altered interregional migration rates on the proportional population distribution.
    • Demonstrated the method's utility in sensitivity analysis for demographic parameters.

    Conclusions:

    • Small changes in regional natural growth rates and interregional migration significantly affect population system outcomes.
    • The analytical framework provides a robust tool for sensitivity analysis in population studies.
    • The methodology is adaptable for analyzing demographic models like the Leslie model, enhancing predictive accuracy.

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