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Simpler Probabilistic Population Forecasts: Making Scenarios Work
Author(s) -
Goldstein Joshua R.
Publication year - 2004
Publication title -
international statistical review
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.051
H-Index - 54
eISSN - 1751-5823
pISSN - 0306-7734
DOI - 10.1111/j.1751-5823.2004.tb00226.x
Subject(s) - probabilistic logic , work (physics) , population , econometrics , statistics , computer science , mathematics , engineering , environmental health , medicine , mechanical engineering
Summary 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.