New Developments in the Methodology of Expert- and Argument-Based Probabilistic Population Forecasting
AbstractAll population projections are based in one form or another on expert judgement about likely future trends, structural continuity, etc. Although experts are clearly superior to lay people in their field of expertise, when it comes to forecasting they may make serious errors and can be as ignorant as anybody. In the context of expert-based probabilistic population projections, this issue is receiving even more attention. In this paper we argue that information about the future cannot be true for the reason that it is being presented by an acknowledged authority (institution or person), nor is it acceptable to resolve scientific issues on the ground of voting or concert. As an alternative we propose the concept of argument-based expert opinion. Under this approach any structural and trend assumption needs to be based on explicit argumentation rather than implicit judgement.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by International Institute for Applied Systems Analysis in its series Working Papers with number ir00020.
Date of creation: Mar 2000
Date of revision:
Contact details of provider:
Postal: A-2361 Laxenburg
Web page: http://www.iiasa.ac.at/Publications/Catalog/PUB_ONLINE.html
More information through EDIRC
This paper has been announced in the following NEP Reports:
- NEP-ALL-2000-05-08 (All new papers)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Pflaumer, Peter, 1988. "Confidence intervals for population projections based on Monte Carlo methods," International Journal of Forecasting, Elsevier, vol. 4(1), pages 135-142.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Thomas Krichel).
If references are entirely missing, you can add them using this form.