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Reconciling Model and Information Uncertainty in Development Appraisal

Author

Listed:
  • Peter Byrne

    (School of Real Estate & Planning, Henley Business School, University of Reading)

  • Pat McAllister

    (School of Real Estate & Planning, Henley Business School, University of Reading)

  • Pete Wyatt

    (School of Real Estate & Planning, Henley Business School, University of Reading)

Abstract

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.

Suggested Citation

  • Peter Byrne & Pat McAllister & Pete Wyatt, 2010. "Reconciling Model and Information Uncertainty in Development Appraisal," Real Estate & Planning Working Papers rep-wp2010-03, Henley Business School, University of Reading.
    • Handle: RePEc:rdg:repxwp:rep-wp2010-03
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    File URL: http://www.henley.reading.ac.uk/rep/fulltxt/0310.pdf
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    Cited by:

    1. Arvydas Jadevicius & Brian Sloan & Andrew Brown, 2013. "Property Market Modelling and Forecasting: A Case for Simplicity," ERES eres2013_10, European Real Estate Society (ERES).

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