The Unexpected Results Produced by a Specific Design of a Probabilistic Population Projection Model

Thomas Salzmann, University of Rostock
Christina Bohk, University of Rostock

The progress from deterministic to probabilistic projection models was an important enhancement to capture forecast uncertainty for the future evolution of the vital rates. But most of these probabilistic or stochastic approaches still capture the forecast uncertainty with some restrictions. In this paper we discuss our findings using different types of one probabilistic population projection model (PPPM). But in spite of following various well-known stochastic projection approaches, we are going to introduce a novel PPPM. This new PPPM does not generate probability via generating assumptions with stochastic models using stochastic Leslie matrices or time series models. Rather, our PPPM focuses on the method of using probability in a complex projection model. Therefore, a different understanding of probability is implemented in our PPPM. The PPPM is a very flexible projection model that takes exogenous assumptions with an occurrence probability into the computation process.