Valuating residential real estate using parametric programming

Subhash C. Narula, John F. Wellington and Stephen A. Lewis

European Journal of Operational Research, 2012, vol. 217, issue 1, 120-128

Abstract: When the estimation of the single equation multiple linear regression model is looked upon as an optimization problem, we show how the principles and methods of optimization can assist the analyst in finding an attractive prediction model. We illustrate this with the estimation of a linear prediction model for valuating residential property using regression quantiles. We make use of the linear parametric programming formulation to obtain the family of regression quantile models associated with a data set. We use the principle of dominance to reduce the number of models for consideration in the search for the most preferred property valuation model (s). We also provide useful displays that assist the analyst and the decision maker in selecting the final model (s). The approach is an interface between data analysis and operations research.

Keywords: Linear programming; Parametric programming; Real estate valuation; Regression; Regression quantiles (search for similar items in EconPapers)
Date: 2012
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Citations: View citations in EconPapers (8)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:217:y:2012:i:1:p:120-128

DOI: 10.1016/j.ejor.2011.08.014

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