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Econometric Support of a Mass Valuation Process

Author

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  • Doszyń Mariusz

    (University of Szczecin, Institute of Economics and Finance, Mickiewicza 64, 71-101Szczecin, Poland)

Abstract

Research background: The issues undertaken in the paper include the specification of an econometric model in real estate mass appraisal. Advantages and disadvantages of using econometric models in real estate mass appraisal are discussed.Purpose: The issue of aiding the valuation process with an econometric model based on the Szczecin algorithm of real estate mass appraisal is discussed in the paper. Such problems like multicollinearity, lack of coincidence and nonmonotonic influence of attributes are pointed out. Also, potential solutions to these problems are mentioned. Moreover, the paper features a discussion of cases in which econometric appraisal is not sufficient.Research methodology: The base for constructing an econometric model is the so-called Szczecin algorithm of real estate mass appraisal. Based on the algorithm, the econometric model was created to enable determining the impact of real estate attributes and location on their value.Results: problems related with specification, estimation and verification of the real estate mass appraisal econometric model are discussed in an empirical example.Novelty: A non-linear model is proposed, which features explanatory variables introduced into the model, and by taking into consideration the scale of their measurement. The proposed model, by introducing dummy variables, also account for the impact of a location, which significantly improves the fit to empirical values.

Suggested Citation

  • Doszyń Mariusz, 2020. "Econometric Support of a Mass Valuation Process," Folia Oeconomica Stetinensia, Sciendo, vol. 20(1), pages 81-94, June.
    • Handle: RePEc:vrs:foeste:v:20:y:2020:i:1:p:81-94:n:5
    DOI: 10.2478/foli-2020-0005
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    References listed on IDEAS

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    1. Jozef Zurada & Alan S. Levitan & Jian Guan, 2011. "A Comparison of Regression and Artificial Intelligence Methods in a Mass Appraisal Context," Journal of Real Estate Research, American Real Estate Society, vol. 33(3), pages 349-388.
    2. W.J. McCluskey & M. McCord & P.T. Davis & M. Haran & D. McIlhatton, 2013. "Prediction accuracy in mass appraisal: a comparison of modern approaches," Journal of Property Research, Taylor & Francis Journals, vol. 30(4), pages 239-265, December.
    3. Widłak, Marta & Waszczuk, Joanna & Olszewski, Krzysztof, 2014. "Spatial and hedonic analysis of house price dynamics in Warsaw," MPRA Paper 60479, University Library of Munich, Germany.
    4. Timothy J. Fik & David C. Ling & Gordon F. Mulligan, 2003. "Modeling Spatial Variation in Housing Prices: A Variable Interaction Approach," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 31(4), pages 623-646, December.
    5. Hans R. Isakson, 1998. "The Review of Real Estate Appraisals Using Multiple Regression Analysis," Journal of Real Estate Research, American Real Estate Society, vol. 15(2), pages 177-190.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    econometric modelling; real estate mass appraisal algorithm; multicollinearity; qualitative variables;
    All these keywords.

    JEL classification:

    • R33 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - Nonagricultural and Nonresidential Real Estate Markets
    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General

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