Simple but flexible stochastic population forecasts based on conditional expert opinions

Francesco C. Billari, Università Bocconi
Rebecca Graziani, Università Bocconi
Eugenio Melilli, Università Bocconi

In this paper we build a formal framework for developing expert-based stochastic population forecasts starting from standard scenario-based population projections. More specifically, we formalize a procedure in which the full probability distribution of forecasts is derived from 1) an initial scenario (which might be based on actual scenarios as available from standard deterministic projections); 2) expert opinions on developments conditional to the realization of high-low scenario. In the final version of the paper a full example will be developed.