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

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Listed:
  • Shawn L. Robey
  • Mark A McKnight
  • Misty R. Price
  • Rachel N. Coleman

Abstract

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.

Suggested Citation

  • Shawn L. Robey & Mark A McKnight & Misty R. Price & Rachel N. Coleman, 2019. "Considerations for a Regression-Based Real Estate Valuation and Appraisal Model: A Pilot Study," Accounting and Finance Research, Sciedu Press, vol. 8(2), pages 1-99, May.
    • Handle: RePEc:jfr:afr111:v:8:y:2019:i:2:p:99
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    References listed on IDEAS

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    1. Zheng Liu & Pengfei Wang & Tao Zha, 2013. "Land‐Price Dynamics and Macroeconomic Fluctuations," Econometrica, Econometric Society, vol. 81(3), pages 1147-1184, May.
    2. Halbert C. Smith, 1986. "Inconsistencies in Appraisal Theory and Practice," Journal of Real Estate Research, American Real Estate Society, vol. 1(1), pages 1-17.
    3. Guo, Zi-Yi, 2017. "Housing Dynamics, Empirical Facts and the Business Cycle," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 12(2), pages 46-53.
    4. Narula, Subhash C. & Wellington, John F. & Lewis, Stephen A., 2012. "Valuating residential real estate using parametric programming," European Journal of Operational Research, Elsevier, vol. 217(1), pages 120-128.
    5. Nghiep Nguyen & Al Cripps, 2001. "Predicting Housing Value: A Comparison of Multiple Regression Analysis and Artificial Neural Networks," Journal of Real Estate Research, American Real Estate Society, vol. 22(3), pages 313-336.
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    More about this item

    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

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