Predicting a house's selling price through inflating its previous selling price

A Brint ()
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A Brint: The University of Sheffield

Journal of the Operational Research Society, 2009, vol. 60, issue 3, 339-347

Abstract: Abstract This paper considers how accurately inflating the previous selling price of a modern property predicts its selling price. Predicting a house's value is an important capability as it allows how the asking price affects the time to sale and the price achieved, to be modelled. The analysis is carried out on a data set of 105 pairs of earlier and later selling prices for UK properties constructed since January 1999. As an alternative to using published house price indices for inflating the prices, a novel approach for modifying the published house price indices through the use of observed repeat sales of properties is put forward and analysed. Using the best published index gives an average predictive error of 10.9% while using the published index modified by repeat-sales information, gives an average predictive error of 8.4%.

Keywords: econometrics; forecasting; markov processes; statistics; urban studies (search for similar items in EconPapers)
Date: 2009
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DOI: 10.1057/palgrave.jors.2602567

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