Stochastic population forecasts based on conditional expert opinions

Area of Science:

• Demography
• Statistical Modeling
• Population Studies

Background:

• Official population forecasts often rely on deterministic scenarios.
• There is a need for probabilistic forecasting methods that incorporate expert knowledge.
• Understanding future population dynamics requires robust forecasting tools.

Purpose of the Study:

• To develop and apply an expert-based stochastic population forecasting methodology.
• To enable the creation of probabilistic versions of official scenario-based forecasts.
• To provide a framework for incorporating expert judgment into demographic projections.

Main Methods:

• Elicitation of expert opinions on demographic components.
• Conditional scenario-based expert opinion gathering (two-step or multi-step).
• Specification of the full probability distribution for population forecasts.

Main Results:

• A novel expert-based stochastic population forecasting method was developed.
• The method was successfully applied to generate a stochastic forecast for the Italian population.
• Probabilistic population projections were derived from official scenarios.

Conclusions:

• Expert-based stochastic forecasting offers a valuable alternative to traditional methods.
• The developed method enhances the probabilistic nature of official population forecasts.
• This approach provides a more comprehensive understanding of future population trends.