Dynamic demographic models and parameter identification: Simulations based on statistical data

Abstract

This paper is concerned with dynamical population models obtained from short and long-term changes in size and age composition due to demographic processes such as births, deaths, migration, etc. Both deterministic and stochastic models are presented. The parameters which are embedded in the models may be either unavailable or noisy, therefore system identification methods are invoked to estimate these parameters. The numerical results presented illustrate that the mathematical models can reproduce the data provided by the Statistic Department of the Republic of Cyprus, and that the unknown and noisy parameters postulated in the models are determined with high accuracy. © 2009 EUCA.