The stochastic method has recently received much attention from researchers and seems to be a useful and efficient tool for implementing multiregional forecasting at a local level. In the paper the results are presented of a project financed by the Province of Rome to make a multiple stochastic population forecast of the Rome Metropolitan Area using the so-called Bertino-Sonnino method, based on micro-simulations of birthdeath- emigration-immigration point event processes. This forecast is based on a range of assumptions referring to the future demographic dynamics over the period 2009-24 and forming three variants. The outcome of the stochastic method is compared with deterministic multiregional forecasting to verify the efficiency of both methodologies. This two-step strategy allows control to be maintained over the assumed future demographic variants, at the same time linking in a probability level.
Stochastic Population Projections: an Application to the Rome Metropolitan Area
Massimiliano Crisci
2014
Abstract
The stochastic method has recently received much attention from researchers and seems to be a useful and efficient tool for implementing multiregional forecasting at a local level. In the paper the results are presented of a project financed by the Province of Rome to make a multiple stochastic population forecast of the Rome Metropolitan Area using the so-called Bertino-Sonnino method, based on micro-simulations of birthdeath- emigration-immigration point event processes. This forecast is based on a range of assumptions referring to the future demographic dynamics over the period 2009-24 and forming three variants. The outcome of the stochastic method is compared with deterministic multiregional forecasting to verify the efficiency of both methodologies. This two-step strategy allows control to be maintained over the assumed future demographic variants, at the same time linking in a probability level.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.