Considerations for a Regression-Based Real Estate Valuation and Appraisal Model: A Pilot Study

Shawn L. Robey, Mark A McKnight, Misty R. Price, Rachel N. Coleman


This paper advocates a more scientific approach to residential real estate valuation as opposed to more traditional approaches, which are flawed for two main reasons: (1) appraiser judgements are almost exclusively used and (2) appraisers’ sample sizes are too small to provide adequate estimated values. By using a regression model, this paper explores the impacts of different characteristics on market value. Three hundred and fifteen properties in Evansville, Indiana, were analyzed testing twelve different variables. This model suggests that 91.8% of the total market value variation is explained by four independent variables. These findings provide evidence that multiple linear regression could be used to better predict a property’s value.

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