Open AccessPrinciples and Criteria for using Statistical Parametric Models and Conditional Models for Valuation of Multi-Component Real Estate
Author(s) -
Tomasz Adamczyk,
Agnieszka Bieda,
Piotr Parzych
Publication year - 2019
Publication title -
real estate management and valuation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.296
H-Index - 8
ISSN - 2300-5289
DOI - 10.2478/remav-2019-0013
Subject(s) - real estate , valuation (finance) , parametric statistics , econometrics , computer science , parametric model , component (thermodynamics) , statistical model , cost approach , economics , mathematics , artificial intelligence , statistics , real estate development , finance , physics , thermodynamics
The complexity of multi-component real properties results from the possibility of identifying various components in legal, physical or functional terms. The possibility of distinguishing various functional elements of real properties, combined with the specificity resulting from their market properties, is problematic when applying the comparative approach to real estate valuation. In this case, the valuation procedure can be implemented using statistical models: the parametric model or the conditional one. This research paper demonstrates the construction of the parametric and conditional models taking into account the geometric and pricing attributes of multi-component real estate. The authors paid attention to adjusting the models to the available market data. They also specified the conditions for the use of statistical models in the real estate valuation process. Based on the analytical and accounting considerations, the estimation criteria for the parametric model and the conditional model were defined, which allow the correct application of these models at the stages of the real estate market analysis and the real estate valuation process.