Conditional Probabilistic Population Forecasting

Sanderson WC, Scherbov S, O'Neill BC, & Lutz W (2003). Conditional Probabilistic Population Forecasting. IIASA Interim Report. IIASA, Laxenburg, Austria: IR-03-052


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Since policy makers often prefer to think in terms of scenarios, the question has arisen as to whether it is possible to make conditional population forecasts in a probabilistic context. This paper shows that it is both possible and useful to make these forecasts. We do this with two different kinds of examples. The first is the probabilistic analog of deterministic scenario analysis. Conditional probabilistic scenario analysis is essential for policy makers it allows them to answer "what if" type questions properly when outcomes are uncertain. The second is a new category that we call "future jump-off date forecasts". Future jump-off date forecasts are valuable because they show policy makers the likelihood that crucial features of today's forecasts will also be present in forecasts made in the future.

Item Type: Monograph (IIASA Interim Report)
Research Programs: World Population (POP)
Depositing User: IIASA Import
Date Deposited: 15 Jan 2016 02:15
Last Modified: 18 Nov 2016 05:43

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