Krzysztof Dmytrów https://orcid.org/0000-0001-7657-6063
ARTICLE

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ABSTRACT

There are situations in the real estate market in which a large number of properties have to be valued at the same time. In such cases it is advisable to use mass valuation methods. These methods involve estimating the value of a property on the basis of the values of the attributes defining it. The aim of the paper is to calibrate the influence of attributes on unit values of properties in mass appraisal in order to minimise the valuation error. The research was conducted for 318 residential properties located in Szczecin. The Szczecin Algorithm of Real Estate Mass Appraisal was used along with the econometric, statistical and expert approaches. The econometric approach is based on the ridge regression model, the statistical approach on the partial Kendall T correlation coefficients, and the expert approach on the AHP method. The quadratic programming was co-employed with the statistical and expert approaches in order to minimise the mean square error (MSE) of the valuations. The econometric and statistical approaches with the minimisation of the MSE generated best results. The least accurate results were obtained by means of the statistical and expert approaches without the minimisation of the MSE. However, even though the optimisation of the MSE improves the quality of valuations, it also narrows down their volatility, which might make the valuation of properties from the outside of a given database more problematic.

KEYWORDS

real estate mass appraisal, real estate attributes, AHP method, statistical and econometric methods of real estate mass appraisal, quadratic programming

JEL

C34, C44, R30

REFERENCES

Apostolou B., Hassell J. M., (1993), An empirical examination of the sensitivity of the analytic hierarchy process to departures from recommended consistency ratios, Mathemmatical. Computer Modelling, 17(4/5), 163–170. DOI: 10.1016/0895-7177(93)90184-Z.

Ball J., Srnivasan V. C., (1994), Using the Analytic Hierarchy Process in House Selection, The Journal of Real Estate Finance and Economics, 9, 69–85. DOI: 10.1007/BF01153589.

Brunelli M., (2015), Introduction to the Analytic Hierarchy Process, Springer, Cham Heidelberg, New York, London. DOI: 10.1007/978-3-319-12502-2.

Calvetti D., Morigi S., Reichel L., Sgallari F., (2000), Tikhonov regularization and the L-curve for large discrete ill-posed problems, Journal of Computational and Applied Mathematics, 123(1–2), 423–446. DOI: 10.1016/S0377-0427(00)00414-3.

Ćetković J., Lakić S., Lazarevska M., Žarković M., Vujošević S., Cvijović J., Gogić M., (2018), Assessment of the Real Estate Market Value in the European Market by Artificial Neural Networks Application, Complexity, (special issue, article ID 1472957), 1–10. DOI: 10.1155/2018/1472957.

Dmytrów K., Gnat S., Kokot S. (2018), Próba uwzględnienia kształtu nieruchomości gruntowych jako atrybutu w procesie zalgorytmizowanej wyceny, Problemy Rynku Nieruchomości, 2(50), 4–10.

Doszyń M., (2017), Statistical Determination of Impact of Property Attributes for Weak Measurement Scales, Real Estate Management and Valuation, 25(4), 75–84. DOI: 10.1515/remav-2017–0031.

Doszyń M., (2018), Ekonometryczna wersja szczecińskiego algorytmu masowej wyceny nieruchomości, Problemy Rynku Nieruchomości, 50(2), 11–17.

Foryś I., Gaca R., (2016), Application of the Likert and Osgood Scales to Quantify the Qualitative Features of Real Estate Properties, Folia Oeconomica Stetinensia, 16(2). 7–16. DOI: 10.1515/foli- 2016-0021.

Guitouni A., Martel J. M., (1998), Tentative guidelines to help choosing an appropriate MCDA method, European Journal of Operational Research, 109(2), 501–521. DOI: 10.1016/S0377- 2217(98)00073-3.

Hozer J., Kokot S., Foryś I., Zwolankowska M., Kuźmiński W., (1999), Ekonometryczny algorytm masowej wyceny nieruchomości gruntowych, Uniwersytet Szczeciński, Szczecin.

Hozer J., Kokot S., Kuźmiński W., (2002), Metody analizy statystycznej rynku w wycenie nieruchomości, Polska Federacja Stowarzyszeń Rzeczoznawców Majątkowych, Warszawa.

Hwang C. L., Yoon K., (1981), Multiple Attribute Decision-Making: Methods and Applications, Springer-Verlag, New York.

Kauko T., D'Amato M., (eds.), (2008), Mass Appraisal Methods: An International Perspective for Property Valuers, Blackwell Publishing, Oxford.

Kolenda M., (2006), Taksonomia numeryczna. Klasyfikacja, porządkowanie i analiza obiektów wielocechowych, Wydawnictwo Akademii Ekonomicznej im. Oskara Langego we Wrocławiu, Wrocław.

Kozioł-Kaczorek D., (2012), Hierarchizacja cech nieruchomości z zastosowaniem analitycznego procesu hierarchicznego, Studia i Materiały Towarzystwa Naukowego Nieruchomości, 20(1), 165– 174.

Nermend K., (2017), Metody analizy wielokryterialnej i wielowymiarowej we wspomaganiu decyzji, Wydawnictwo Naukowe PWN, Warszawa.

Parker R. I., Vannest K. J., Davis J. L., Sauber S. B., (2011), Combining Nonoverlap and Trend for Single-Case Research: Tau-U, Behavior Therapy, 42(2), 284–299. DOI: 10.1016/j.beth. 2010.08.006.

Saaty T. L., (1980), The Analytic Hierarchy Process, McGraw-Hill, New York.

Saaty T. L., (1990), How to make a decision: The analytic hierarchy process, European Journal of Operational Research, 48(1), 9–26. DOI: 10.1016/0377-2217(90)90057-I.

Saaty T. L., Ergu D., (2015), When is a Decision-Making Method Trustworthy? Criteria for Evaluating Multi-Criteria Decision-Making Methods, International Journal of Information Technology & Decision Making, 14(6), 1171–1187. DOI: 10.1142/S021962201550025X.

Triantaphyllou E., (2000), Multi-criteria decision-making methods: A comparative study, Kluwer Academic Publishers, London. DOI: 10.1007/978-1-4757-3157-6.

Trzaskalik T., (ed.), (2014), Wielokryterialne wspomagania decyzji. Metody i zastosowania, Polskie Wydawnictwo Ekonomiczne, Warszawa.

Yalpir S., (2014), Forecasting residential real estate values with AHP method and integrated GIS, in: Conference proceedings of People, Buildings and Environment, an international scientific conference, Kroměříž, Czech Republic, 694–706.

Źróbek S., Bełej M., (2000), Podejście porównawcze w szacowaniu nieruchomości, Educaterra, Olsztyn.

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