This study investigates the relationship between the rental and sales segments of the housing market in the city of Rome (Italy), with a specific focus on the role of building energy efficiency and technological systems features. Although renting and buying are driven by distinct market drivers, both segments increas-ingly respond to sustainability-oriented and comfort-enhancing attributes. Under-standing how these characteristics are appreciated across markets is fundamental for interpreting household choices, investor behaviour and policy effectiveness. The proposed methodological approach develops two separate econometric eval-uation models, i.e. one for the sales market (BUY model) and one for the rental market (RENT model), to identify the most influential energy-related variables and building technological systems factors to quantify their marginal contribu-tion to housing prices and rents. The two comparable datasets are constructed for properties sold and rented within the same urban context, specifically focusing on the following variables: energy performance label, central heating systems, photovoltaic installations, air conditioning systems and building automation tech-nologies. Energy efficiency and technological factors have notable impacts on each housing segment, though with different intensities and directions. Overall, the findings highlight differentiated market appreciation of sustainable housing features and demonstrate the effectiveness of the flexible data-driven approach in capturing the cross-market dynamics.

Rent and Buy Market Interactions: a Focus on Energy Performance and Building Technological Systems / Morano, P., Di Liddo, F., Ruggeri, A., Tajani, F., Emmi, G.. - (2027). (International Conference on Computational Science and Its Applications (ICCSA) 2026 Braga (Portogallo) ).

Rent and Buy Market Interactions: a Focus on Energy Performance and Building Technological Systems

Francesco Tajani;
2027

Abstract

This study investigates the relationship between the rental and sales segments of the housing market in the city of Rome (Italy), with a specific focus on the role of building energy efficiency and technological systems features. Although renting and buying are driven by distinct market drivers, both segments increas-ingly respond to sustainability-oriented and comfort-enhancing attributes. Under-standing how these characteristics are appreciated across markets is fundamental for interpreting household choices, investor behaviour and policy effectiveness. The proposed methodological approach develops two separate econometric eval-uation models, i.e. one for the sales market (BUY model) and one for the rental market (RENT model), to identify the most influential energy-related variables and building technological systems factors to quantify their marginal contribu-tion to housing prices and rents. The two comparable datasets are constructed for properties sold and rented within the same urban context, specifically focusing on the following variables: energy performance label, central heating systems, photovoltaic installations, air conditioning systems and building automation tech-nologies. Energy efficiency and technological factors have notable impacts on each housing segment, though with different intensities and directions. Overall, the findings highlight differentiated market appreciation of sustainable housing features and demonstrate the effectiveness of the flexible data-driven approach in capturing the cross-market dynamics.
2027
International Conference on Computational Science and Its Applications (ICCSA) 2026
rental market; sale market; real estate; energy performance; EPC label; building automation; photovoltaic panels; influencing factors; econometric analysis
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
Rent and Buy Market Interactions: a Focus on Energy Performance and Building Technological Systems / Morano, P., Di Liddo, F., Ruggeri, A., Tajani, F., Emmi, G.. - (2027). (International Conference on Computational Science and Its Applications (ICCSA) 2026 Braga (Portogallo) ).
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1771080
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