Conditional Probabilistic Population Forecasting

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http://eprints.org/relation/isVersionOf https://pure.iiasa.ac.at/id/document/4928 http://eprints.org/relation/isVolatileVersionOf https://pure.iiasa.ac.at/id/document/4928 http://eprints.org/relation/isCoversheetVersionOf https://pure.iiasa.ac.at/id/document/4928 archive 351 disk0/00/00/70/31 2016-01-15 02:15:48 2023-08-05 05:00:37 2016-01-15 02:15:48 monograph show 3 Sanderson W.C. 1631 Scherbov S. 7113 0000-0002-0881-1073 O'Neill B.C. 7542 Lutz W. 1124 0000-0001-7975-8145 Conditional Probabilistic Population Forecasting pub iis_pop prog_pop 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. 2003-10 published IR-03-052 IR-03-052 265 270 1492 190 public interim_report IIASA, Laxenburg, Austria 17 FALSE info:eu-repo/semantics/book