Abstract
Europe faces a situation where housing represents the main savings for most of the population, while the majority of homeowners are seniors aged over 65. The desire to supplement pensions has led to a growing interest in generating income from these savings, with bare ownership emerging as a notable option. This solution makes it possible to transfer the ownership of the home while maintaining usufruct rights for the duration of the owner’s lifetime. This paper examines the status of bare ownership in the city of Rome by web scraping the house offers published on web portals and segmenting those offered as bare ownership. Machine learning analysis based on neural networks and binary logit regression allows for the observation of the particular behavior of the housing supply in bare ownership; it shows the different intrinsic and extrinsic characteristics that determine this Real Estate segment. The findings highlight the development of a growing market strongly influenced by the location of assets. These findings provide valuable insights for both investors and urban planners regarding changes in urban dynamics processes.
Published Version
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