NON-RESIDENTIAL REAL ESTATE PRICES AND MACHINE LEARNING: THE HOW AND THE WHY

Raffaella Barone

No 25238, BAFFI CAREFIN Working Papers from BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy

Abstract: This paper examines the relationship between non-residential property prices and various social, economic, and environmental indicators within the provinces where these properties are located. We focus on indicators from the Eni Enrico Mattei Foundation and SDSN Italia that track the 17 sustainable development goals, as well as additional factors like crime rates, per capita GDP, and sales frequency. Using a machine learning algorithm, we predicted property sale prices and applied SHapley Additive exPlanations to assess the importance of each variable. Our findings highlight the strong influence of categorical variables and SDG indicators on prices. Finally, we used causal inference to explore how policy interventions might affect property prices.

Keywords: Machine Learning; Real estate market; Financial Stability; Sustainability; Crimes (search for similar items in EconPapers)
JEL-codes: B4 C1 G01 R33 (search for similar items in EconPapers)
Pages: 37
Date: 2025
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