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Christina Bohk, Roland Ewald, and Adelinde M Uhrmacher (2009)

Probabilistic Population Projection with James II

In: Proceedings of the Winter Simulation Conference, ed. by M. D. Rossetti and R. R. Hill and B. Johansson and A. Dunkin and R. G. Ingalls, pp. 2008-2019, IEEE Computer Science.

Predicting future populations and their structure is a central theme in demography. It is related to public health issues, political decision-making, or urban planning. Since these predictions are concerned with the evolution of a complex system, they exhibit a considerable uncertainty. Accounting for this inherent uncertainty is crucial for subsequent decision processes, as it reveals the range of possible outcomes and their likelihood. Consequently, probabilistic prediction approaches emerged over the past decades. This paper describes the probabilistic population projection model (PPPM), a recently developed method that allows detailed projections, but has a complex structure and requires much input data. We discuss the development of P3J, a tool that helps users in managing and executing projections and is built on top of the simulation system JAMES II. We outline how even specific tools like P3J profit from general-purpose simulation frameworks like JAMES II, and illustrate its usage by a simple example.