UDC 519.86
This article analyzes the main factors influencing residential property prices in the city of Perm. To quantitatively assess the impact of various apartment characteristics on their market value, methods of multiple regression and variance analysis are applied. Econometric pricing models are developed, considering both vertical differentiation (market segmentation by housing class) and horizontal (territorial) stratification. The modeling results demonstrate that in elite market segments, qualitative parameters and housing size have a decisive impact on prices, whereas in mass segments, apartment compactness and infrastructure accessibility play a significant role. Thus, mathematical modeling serves as a tool for verifying value-based correspondences in pricing: price differences largely align with variations in property characteristics. The study results can be used for price forecasting and developing strategies for balanced urban environment development.
econometric modeling, housing market, pricing, regression analysis, variance analysis, market segmentation, vertical stratification, horizontal stratification, Perm
1. Data.mendeley.com [Elektronnyy resurs]. Rezhim dostupa: https://data.mendeley.com/datasets/2rxrnvgfym/1 (data obrascheniya: 04.06.2024).
2. Bureeva N. N. Mnogomernyy statisticheskiy analiz s ispol'zovaniem PPP “STATISTICA”. – Uchebno-metodicheskiy material. – Nizhniy Novgorod: NNGU, 2007. – 112 s.
3. Yudenkov V. A. Dispersionnyy analiz. – Minsk: Biznesofset, 2013. – 22 s.
4. Efendiev A. N. ISPOL'ZOVANIE METODOV REGRESSIONNOGO ANALIZA PRI OCENKE STOIMOSTI KVARTIR // Nauchnyy zhurnal molodyh uchenyh. 2019. №3 (16). URL: https://cyberleninka.ru/article/n/ispolzovanie-metodov-regressionnogo-analiza-pri-otsenke-stoimosti-kvartir (data obrascheniya: 20.05.2025).
5. Bochenina, M. V. Ocenka izmeneniya cen na rynke zhil'ya: gedonicheskiy podhod / M. V. Bochenina // Vestnik evraziyskoy nauki. — 2022. — T. 14. — № 3. — URL: https://esj.today/PDF/48ECVN322.pdf
6. Ostrikova A.L., Selyutin V.V. Innovacionnye tehnologii massovoy ocenki zhiloy nedvizhimosti // Sistemnyy analiz i modelirovanie ekonomicheskih i ekologicheskih sistem. – 2023. – Vyp. 8. – S. 147–154.
7. Caudill S. B., Manage N. D., Mixon F. G. Using Co-Ordinate Systems in Hedonic Housing Regressions // Real Estate. 2024. Vol. 10. No. 1. P. 4–15. DOI:https://doi.org/10.3390/realestate1010004.
8. Jaroszewicz J., Horynek H. Aggregated Housing Price Predictions with No Information About Structural Attributes—Hedonic Models: Linear Regression and a Machine Learning Approach // Land.– 2024. – Vol. 13, No. 11. – Article 1881.
9. Keskin B. Multilevel approach to the analysis of housing submarkets // Regional Studies, Regional Science. – 2022. – Vol. 9, No. 1. – pp. 264–279.
