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“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

Laura Gabrielli (), Aurora Greta Ruggeri and Massimiliano Scarpa
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Laura Gabrielli: Department of Architecture and Arts, University IUAV of Venice, Dorsoduro 2206, 30123 Venice, Italy
Aurora Greta Ruggeri: Department of Architecture and Arts, University IUAV of Venice, Dorsoduro 2206, 30123 Venice, Italy
Massimiliano Scarpa: Department of Architecture and Arts, University IUAV of Venice, Dorsoduro 2206, 30123 Venice, Italy

Land, 2023, vol. 12, issue 6, 1-23

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.

Keywords: market value; value assessment; multiple regression; location; fixed effects; computer programming; random forest; diachronic analysis (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2023
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