Dynamic flow modeling with interregional dependency effects: an application to structural change in the U.S....

Area of Science:

• Demography
• Sociology
• Geospatial Analysis

Background:

• Population dynamics and migration are complex phenomena.
• Understanding interregional migration is crucial for policy and planning.
• Existing methods may not fully capture the dynamics of migration flows.

Purpose of the Study:

• To apply causative matrix methods to analyze U.S. interregional migration patterns.
• To monitor and forecast population changes and migration trends.
• To examine the strengths of interregional dependencies over time.

Main Methods:

• Utilizing causative matrix methods for population projection and migration analysis.
• Analyzing column sums and eigenvalues to gauge regional shift strengths.
• Examining gross migration streams and net migration patterns.

Main Results:

• Causative matrix methods provide insights into interregional dependency effects.
• Analysis revealed trends in U.S. interregional migration from 1935 to 1982.
• Observed shifts in core-periphery migration and outflow source areas.

Conclusions:

• Causative matrix methods are effective for monitoring and forecasting migration.
• The study highlights significant temporal changes in U.S. migration patterns.
• This approach offers a comprehensive view of population movement dynamics.