The traditional high-low-medium scenario approach to quantifying
uncertainty in population forecasts has been criticized as lacking
probabilistic meaning and consistency. This paper shows, under
certain assumptions, how appropriately calibrated scenarios can be
used to approximate the uncertainty intervals on future population
size and age structure obtained with fully stochastic
forecasts. As many forecasting organizations already produce
scenarios and because dealing with them is familiar territory,
the methods presented here offer an attractive intermediate
position between probabilistically inconsistent scenario analysis
and fully stochastic forecasts.
Publié le : 2004-04-14
Classification:
Age structure,
Population forecasting,
Population size,
Scenarios,
Stochastic,
Uncertainty
@article{1079360116,
author = {Goldstein, Joshua R.},
title = {Simpler Probabilistic Population Forecasts: Making Scenarios Work},
journal = {Internat. Statist. Rev.},
volume = {72},
number = {1},
year = {2004},
pages = { 93-106},
language = {en},
url = {http://dml.mathdoc.fr/item/1079360116}
}
Goldstein, Joshua R. Simpler Probabilistic Population Forecasts: Making Scenarios Work. Internat. Statist. Rev., Tome 72 (2004) no. 1, pp. 93-106. http://gdmltest.u-ga.fr/item/1079360116/