Population Development of the Rhine-Neckar Metropolitan Area: A Stochastic Population Forecast on the Basis of Functional Data Analysis

Abstract

Stochastic population forecasts are gaining popularity in these times of demographic change, as compared with the scenario technique frequently used for projections, they provide important additional information: the forecasted population lies within a prediction interval to which a probability of occurrence can be allocated. However, this approach requires long time-series and detailed information about the determinants of population development (fertility, mortality and net migration), which are frequently not available in sufficient depth at the regional level, but are generally subsumed into age groups. Stochastic population forecasts are therefore usually limited to the national level. Nonetheless, methods of functional data analysis enable us to disaggregate the required demographic variables into years of age and to use them as the data basis of a stochastic model, also at the regional level. This essay presents this approach and models based on it using the example of the population development of the Rhine-Neckar metropolitan area in Germany.