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2020 | vol. 20, iss. 1 | 81--94
Tytuł artykułu

Econometric Support of a Mass Valuation Process

Autorzy
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
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. (original abstract)
Rocznik
Strony
81--94
Opis fizyczny
Twórcy
  • University of Szczecin, Poland
Bibliografia
  • Barańska, A., (2010). Statystyczne metody analizy i weryfikacji proponowanych algorytmów wyceny nieruchomości [Statistical Methods of Analysis and Verification of Proposed Property Valuation Algorithms]. Rozprawy, Monografie, 214. Kraków: Wydawnictwa AGH.
  • Benjamin, J.D., Randall, S., Guttery, R.S., Sirmans, C.F. (2004). Mass Appraisal: An Introduction to Multiple Regression Analysis for Real Estate Valuation. Journal of Real Estate Practice and Education, 7 (1), 65-77.
  • Cellmer, R. (2013). Use of Spatial Autocorrelation to Build Regression Models of Transaction Prices. Real Estate Management and Valuation, 21 (4), 65-74.
  • Czaja, J. (2001). Metody szacowania wartości rynkowej i katastralnej nieruchomości [Methods of Estimating the Market and Cadastral Value of Real Estate]. Kraków: Komp-System.
  • Dell, G. (2017). Regression, Critical Thinking, and the Valuation Problem Today. Appraisal Journal, 85 (3), 217-230.
  • Doszyń, J., Hozer, J. (2017). Szczeciński algorytm masowej wyceny nieruchomości - podejście ekonometryczne [Szczecin Algorithm of Real Estate Mass Valuation - Econometric Approach]. Studia i Prace WNEiZ US, 50 (1), 19-30.
  • Doszyń, M. (2012). Ekonometryczna wycena nieruchomości [Econometric Real Estate Appraisal]. Metody Ilościowe w Ekonomii, Studia i Prace Wydziału Nauk Ekonomicznych i Zarządzania, 26.
  • Doszyń, M. (2017). Statistical Determination of Impact of Property Attributes for Weak Measurement Scales. Real Estate Management and Valuation, 25 (4), 75-84.
  • Fik, T.J., Ling, D.C., Mulligan, G.F. (2003). Modelling Spatial Variation in Housing Prices: A Variable Interaction Approach. Real Estate Economics, 31 (4), 623-646.
  • Greene, W.H. (2003), Econometric Analysis, 5th edition, Prentice Hall.
  • Hozer, J., Foryś, I., Zwolankowska, M., Kokot, S., Kuźmiński, W. (1999). Ekonometryczny algorytm masowej wyceny nieruchomości gruntowych [Econometric Algorithm of Land Properties Mass Valuation]. Szczecin: Katedra Ekonometrii i Statystyki Uniwersytetu Szczecińskiego, Stowarzyszenie Pomoc i Rozwój.
  • Hozer, J., Kokot, S., Kuźmiński, W. (2002). Metody analizy statystycznej rynku w wycenie nieruchomości [Methods of Statistical Market Analysis in Real Estate Valuation]. Warszawa: Polska Federacja Stowarzyszeń Rzeczoznawców Majątkowych.
  • Isakson, H.R. (1998). The Review of Real Estate Appraisals Using Multiple Regression Analysis. Journal of Real Estate Research, 15 (2), 177-190.
  • Judge, G.G., Takayama, T. (1966). Inequality Restrictions in Regression Analysis. Journal of the American Statistical Association, 61 (313), 166-181.
  • Kauko, T., d'Amato, M. (ed.) (2008), Mass Appraisal Methods: An International Perspective for Property Valuers. Blackwell Publishing Ltd.
  • McCluskey, W.J., McCord, M., Davis, P.T., Haran, M., McIllhatton, D. (2013). Prediction Accuracy in Mass Appraisal: A Comparison of Modern Approaches. Journal of Property Research, 30 (4), 239-265.
  • Pace, R.K., Gilley, O.W. (1990). Estimation Employing A Priori Information Within Mass Appraisal and Hedonic Pricing Models. The Journal of Real Estate Finance and Economics, 3, 55-72.
  • Pagourtzi, E., Assimakopoulos, V., Hatzichristos, T., French, N. (2003). Real Estate Appraisal: a Review of Valuation Methods. Journal of Property Investment & Finance, 21 (4), 383-401.
  • Parzych, P., Czaja, J. (2015). Szacowanie rynkowej wartości nieruchomości [Estimating of Real Estate Market Value]. Kraków: Wydawnictwa AGH.
  • Widłak, M., Waszczuk, J., Olszewski, K. (2015). Spatial and Hedonic Analysis of House Price Dynamics in Warsaw. NBP Working Paper, 197.
  • Zurada, J., Levitan, A.S., Guan, J. (2011). A Comparison of Regression and Artificial Intelligence Methods in a Mass Appraisal Context. Journal of Real Estate Research, 3, 349-387.
Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.ekon-element-000171598885

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