Reconciling model and information uncertainty in development appraisal

[thumbnail of 0310.pdf]
Preview
Text - Published Version
· Please see our End User Agreement before downloading.
| Preview

Please see our End User Agreement.

It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing.

Add to AnyAdd to TwitterAdd to FacebookAdd to LinkedinAdd to PinterestAdd to Email

Byrne, P., McAllister, P. and Wyatt, P. orcid id iconORCID: https://orcid.org/0000-0002-9091-2729, (2010) Reconciling model and information uncertainty in development appraisal. Working Papers in Real Estate & Planning. 03/10. Working Paper. University of Reading, Reading. pp26.

Abstract/Summary

This paper investigates the effect of choices of model structure and scale in development viability appraisal. The paper addresses two questions concerning the application of development appraisal techniques to viability modelling within the UK planning system. The first relates to the extent to which, given intrinsic input uncertainty, the choice of model structure significantly affects model outputs. The second concerns the extent to which, given intrinsic input uncertainty, the level of model complexity significantly affects model outputs. Monte Carlo simulation procedures are applied to a hypothetical development scheme in order to measure the effects of model aggregation and structure on model output variance. It is concluded that, given the particular scheme modelled and unavoidably subjective assumptions of input variance, simple and simplistic models may produce similar outputs to more robust and disaggregated models.

Item Type Report (Working Paper)
URI https://reading-clone.eprints-hosting.org/id/eprint/26995
Divisions Henley Business School > Real Estate and Planning
Publisher University of Reading
Download/View statistics View download statistics for this item

Downloads

Downloads per month over past year

University Staff: Request a correction | Centaur Editors: Update this record

Search Google Scholar