“Location, Location, Location”: Fluctuations in Real Estate Market Values after COVID-19 and the War in Ukraine Based on Econometric and Spatial Analysis, Random Forest, and Multivariate Regression

Author:

Gabrielli Laura1ORCID,Ruggeri Aurora Greta1ORCID,Scarpa Massimiliano1

Affiliation:

1. Department of Architecture and Arts, University IUAV of Venice, Dorsoduro 2206, 30123 Venice, Italy

Abstract

In this research, the authors aim to detect the marginal appreciation of construction and neighbourhood characteristics of property prices at three different time points: before the COVID-19 pandemic, two years after the first COVID-19 alert but before the War in Ukraine, and one year after the outbreak of the War. The marginal appreciations of the building’s features are analysed for a pilot case study in Northern Italy using a Random Forest feature importance analysis and a Multivariate Regression. Several techniques are integrated into this study, such as computer programming in Python language, multi-parametric value assessment techniques, feature selection procedures, and spatial analysis. The results may represent an interesting ongoing monitoring of how these anomalous events affect the buyer’s willingness to pay for specific characteristics of the buildings, with particular attention to the location features of the neighbourhood and accessibility.

Publisher

MDPI AG

Subject

Nature and Landscape Conservation,Ecology,Global and Planetary Change

Reference113 articles.

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2. Wang, A., and Xu, Y. (2018, January 26–27). Multiple linear regression analysis of real estate price. Proceedings of the International Conference on Robots and Intelligent System, ICRIS 2018, Changsha, China.

3. Nonlinear regression model and option analysis of real estate price;Feng;Dalian Ligong Daxue Xuebao/J. Dalian Univ. Technol.,2017

4. Bertazzon, S. (2022). L’ Analisi Spaziale. La Geografia Che … Conta, FrancoAngeli.

5. Simonotti, M. (2006). Metodi di Stima Immobiliare, Flaccovio.

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