Population forecasts and confidence intervals for Sweden: a comparison of model-based and empirical approaches

Area of Science:

• Demography
• Population Dynamics
• Statistical Modeling

Background:

• Accurate population size forecasting is crucial for policy and resource allocation.
• Understanding and quantifying uncertainty in population projections is a significant challenge in demography.

Purpose of the Study:

• To compare diverse methods for generating confidence intervals in population size forecasts.
• To evaluate the performance of demographic models versus empirical analyses in estimating forecast uncertainty.

Main Methods:

• Utilized a demographic model for age-structured populations with stochastic vital rates.
• Conducted empirical analyses of historical population forecasts for Sweden (1780-1980).
• Generated and compared confidence intervals from distinct methodological approaches.

Main Results:

• Confidence intervals generated by different methods showed substantial variation.
• The relative sizes of confidence intervals differed across historical periods.
• Empirical analyses and demographic models produced distinct ranges of uncertainty estimates.

Conclusions:

• No single method provides a definitive measure of forecast uncertainty.
• A range of confidence intervals is necessary due to data limitations and incomplete theoretical understanding.
• Uncertainty applies to both population forecasts and their associated uncertainty estimates.