Use of Statistical Models for Simulating Transactions on the Real Estate Market

Radosław Cellmer 1  and Katarzyna Szczepankowska 2
  • 1 assoc. prof., PhD The Faculty of Geodesy, Geospatial and Civil Engineering University of Warmia and Mazury in Olsztyn
  • 2 M. Sc. The Faculty of Geodesy, Geospatial and Civil Engineering University of Warmia and Mazury in Olsztyn


The regularities and relations between real estate prices and the factors that shape them may be presented in the form of statistical models, thanks to which the diagnosis and prediction of prices is possible. A formal description of empirical observation presented in the form of regressive models also offers a possibility for creating certain phenomena in a virtual dimension. Market phenomena cannot be fully described with the use of determinist models, which clarify only a part of price variation. The predicted price is, in this situation, a special case of implementing a random function. Assuming that other implementations are also possible, regressive models may constitute a basis for simulation, which results in the procurement of a future image of the market.

Simulation may refer both to real estate prices and transaction prices. The basis for price simulation may be familiarity with the structure of the analyzed market data. Assuming that this structure has a static character, simulation of real estate prices is performed on the basis of familiarity with the probability distribution and a generator of random numbers. The basis for price simulation is familiarity with model parameters and probability distribution of the random factor.

The study presents the core and theoretical description of a transaction simulation on the real estate market, as well as the results of an experiment regarding transaction prices of office real estate located within the area of the city of Olsztyn. The result of the study is a collection of virtual real properties with known features and simulated prices, constituting a reflection of market processes which may take place in the near future. Comparison between the simulated characteristic and actual transactions in turn allows the correctness of the description of reality by the model to be verified.

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  • ACZEL A. D., 2000, Statystyka w zarządzaniu (Statistics in management), PWN Warszawa

  • ADAMCZEWSKI Z., 2006, Elementy modelowania matematycznego w wycenie nieruchomości. Podejście porównawcze (Elements of mathematical modeling in real estate appraisal. Comparative approach), Oficyna Wydawnicza Politechniki Warszawskiej

  • BAO H., CHONG, A.Y.L, WANG H., WANG L., HUANG Y., 2012, Quantitative Decision making in land banking: A case study on China’s Real Estate Developers via Monte Carlo Simulation, International Journal of Strategic Property Management, Vol. 16(4), 355-269.

  • BARAŃSKA A., 2010, Statystyczne metody analizy i weryfikacji proponowanych algorytmów wyceny nieruchomości (Statistical methods of analysis and veryfication proposed algorithms of valuation), Rozprawy i Monografie, Wydawnictwa AGH, Kraków

  • 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, Vol. 7, No. 1, pp. 65-77

  • BITNER A., 2007, Konstrukcja modelu regresji wielorakiej przy wycenie nieruchomości (The construction of the multiple regression model for the valuation of real estate), Acta Scientiarum Polonorum, Administratio Locorum, No. 6(4), 59-66.

  • CELLMER R., SZCZEPANKOWSKA K. 2014, Simulation modeling in a real estate market, 9th International Conference “Environmental Engineering” Vilnius Gediminas Technical University, May 22-23,

  • CZAJA J., 2001, Metody szacowania wartości rynkowej i katastralnej (Methods for estimating the market and cadastral value), Komp-System, Kraków

  • CZAJA J., LIGAS M., 2010, Zaawansowane metody analizy statystycznej rynku nieruchomości (Advanced statistical analysis for real etstate market research), Studia i Materiały Towarzystwa Naukowego Nieruchomości, Vol. 18, No. 1, pp. 7-20

  • DIAPPI L., BOLCHI P.,2008 Smith's Rent gap Theory and Local Real Estate Dynamics: A Multi-agent Model. Computers, Environment and Urban Systems, 32(1), pp. 6-18

  • HOZER J., KOKOT S., KUŹMIŃSKI W., 2002, Metody analizy statystycznej rynku w wycenie nieruchomości (Methods of statistical analysis in real estate appraisal), Polska Federacja Stowarzyszeń Rzeczoznawców Majątkowych, Warszawa

  • ISAKSON H. R., 1998, The Review of Real Estate Appraisals Using Multiple Regression Analysis, Journal of Real Estate Research, Vol. 15, Issue 2, pp. 177-190

  • MC BREEN J., GOFFETTE-NAGOT F., JENSEN P., 2011, Information and Search on the Housing Market: An Agent-based Model, ERSA conference papers ersa11p1395, European Regional Science Association.

  • PAWLUKOWICZ R., 2006, Użyteczność modeli ekonometrycznych w wycenie nieruchomości - polskie i zagraniczne opinie (The utility of econometric models in the valuation of real estate - Polish and foreign opinions), Zeszyty Naukowe Uniwersytetu Szczecińskiego Nr 450, Prace Katedry Ekonometrii i Statystyki, No. 17, pp. 453-466

  • RAO C. R., TOUTENBURG H., SHALABH, NEUMANN C., 2007, Linear Models and Generalizations: Least Squares and Alternatives, Springer-Verlag, New York

  • SAWIŁOW E., 2010, Problematyka określania wartości nieruchomości metodą analizy statystycznej rynku (The problems of qualifying the value of real estate with the method of the statistical analysis of the market), Studia i Materiały Towarzystwa Naukowego Nieruchomości, Vol. 8, No. 1, pp. 21-32

  • SIRMANS G. S., MACPHERSON D. A., ZIETZ E. N., 2005, The Composition of Hedonic Pricing Models, Journal of Real Estate Literature, Vol. 13, No. 1, pp. 3-46.

  • VOREL J., 2014, Residential location choice modelling: a micro-simulation approach, AUC Geographica, 49, No. 1, pp. 83-97


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