Conditional Probabilistic Population Forecasting

Abstract

Since policy-makers often prefer to think in terms of alternative scenarios,the question has arisen as to whether it is possible to make conditionalpopulation forecasts in a probabilistic context. This paper shows that it isboth possible and useful to make these forecasts. We do this with two differentkinds of examples. The first is the probabilistic analog of deterministicscenario analysis. Conditional probabilistic scenario analysis is essentialfor policy-makers because it allows them to answer “what if” typequestions properly when outcomes are uncertain. The second is a newcategory that we call “future jump-off date forecasts”. Future jump-offdate forecasts are valuable because they show policy-makers the likelihoodthat crucial features of today’s forecasts will also be present in forecastsmade in the future.