Neural Networks Modelling of Municipal Real Estate Market Rent Rates

Muczyński Andrzej () and Walacik Marek ()
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Muczyński Andrzej: University of Warmia and Mazury in Olsztyn, The Faculty of Geodesy, Geospatial and Civil Engineering, Department of Real Estate Resources, Prawocheńskiego Street 15, 10-724 Olsztyn, Poland
Walacik Marek: University of Warmia and Mazury in Olsztyn, The Faculty of Geodesy, Geospatial and Civil Engineering, Department of Land Management and Regional Development, Prawocheńskiego Street 15, 10-724 Olsztyn, Poland

Folia Oeconomica Stetinensia, 2016, vol. 16, issue 2, 17-28

Abstract: This paper presents the results of research on the application of neural networks modelling of municipal real estate market rent rates. The test procedure was based on selected networks trained on the local real estate market data and transformation of the detected dependencies – through established models – to estimate the potential market rent rates of municipal premises. On this basis, the assessment of the adequacy of the actual market rent rates of municipal properties was made. Empirical research was conducted on the local real estate market of the city of Olsztyn in Poland. In order to describe the phenomenon of market rent rates formation an unidirectional three-layer network and a network of radial base was selected. Analyses showed a relatively low degree of convergence of the actual municipal rent rents with potential market rent rates. This degree was strongly varied depending on the type of business ran on the property and its’ social and economic impact. The applied research methodology and the obtained results can be used in order to rationalize municipal property management, including the activation of rental policy.

Keywords: municipal real estate stock management; artificial neural networks; property rent market (search for similar items in EconPapers)
JEL-codes: C45 R33 (search for similar items in EconPapers)
Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:vrs:foeste:v:16:y:2016:i:2:p:17-28:n:2

DOI: 10.1515/foli-2016-0022

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