Using population register data and capture-recapture models to estimate over-coverage in Sweden

Area of Science:

• Demography
• Statistical Modeling
• Population Studies

Background:

• Over-coverage in population registers leads to inaccurate population size estimates.
• Existing methods like Multiple Systems Estimation (MSE) have limitations with longitudinal data.
• Accurate population data is crucial for policy and decision-making.

Purpose of the Study:

• To develop a novel capture-recapture (CR) modeling framework for population registers.
• To estimate annual population size and individual presence probabilities.
• To quantify demographic influences on migration patterns and over-coverage.

Main Methods:

• Developed a capture-recapture (CR) modeling framework.
• Applied the framework to a case study using Swedish population register data.
• Analyzed individual time-series data to model demographic events.

Main Results:

• The CR approach provides more realistic population size estimates compared to deterministic methods.
• The model accurately estimates individual presence probabilities and migration effects.
• The framework offers enhanced insights into individual migration patterns.

Conclusions:

• Capture-recapture modeling offers a superior method for estimating population size and over-coverage from registers.
• The developed framework improves demographic analysis, particularly for dynamic populations.
• This approach enhances understanding of migration dynamics and population register accuracy.