Conditional probabilistic population forecasting

Sanderson, W.C., Scherbov, S. ORCID:, O'Neill, B.C., & Lutz, W. ORCID: (2004). Conditional probabilistic population forecasting. International Statistical Review 72 (2) 157-166. 10.1111/j.1751-5823.2004.tb00230.x.

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Since policy-makers often prefer to think in terms of alternative 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 because 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: Article
Uncontrolled Keywords: Forecasting; Population forecasting; Probabilistic forecasting; Scenarios; Scenario analysis
Research Programs: World Population (POP)
Bibliographic Reference: International Statistical Review; 72(2):157-166 (August 2004)
Depositing User: IIASA Import
Date Deposited: 15 Jan 2016 02:16
Last Modified: 05 Aug 2023 05:00

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