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Uncertainty variants of population forecasts.
Summary
Population forecasts must include uncertainty. The Netherlands Central Bureau of Statistics uses low and high variants, based on past forecast errors, to estimate confidence intervals for total population size.
Area of Science:
- Demography
- Statistical Modeling
- Population Studies
Background:
- Population forecasts are essential for planning but inherently uncertain.
- Previous methods for quantifying forecast uncertainty were insufficient.
- The Netherlands Central Bureau of Statistics (CBS) provides forecast variants to indicate uncertainty.
Purpose of the Study:
- To quantify the uncertainty in population forecasts.
- To develop a method for estimating confidence intervals for total population size.
- To analyze the variability of forecast errors.
Main Methods:
- Analysis of previous forecast errors to determine the width of variant intervals.
- Development of a statistical time-series model specifically for forecast errors in total population growth.
- Estimation of confidence intervals for total population size based on the model.
Main Results:
- The degree of uncertainty in population forecast results varies significantly.
- A statistical time-series model effectively estimates forecast errors.
- Confidence intervals for total population size can be reliably estimated.
Conclusions:
- Acknowledging and quantifying forecast uncertainty is crucial for accurate population projections.
- Statistical modeling provides a robust framework for estimating uncertainty in demographic forecasts.
- The CBS's approach of using variants, informed by error analysis, enhances the utility of population forecasts.