Analysing (A)Symmetries In Student Accommodation Pricing: Evidence From European Student Accommodation Market

This paper examines the relationship between student housing attributes and the pricing of student accommodation. The paper further explores the asymmetries in pricing for Purpose- built Student Accommodation (PBSA) and Private Student Accommodation Providers (PSAP). We utilise a web scraping procedure to access online-listed property information and prices from 25 major student destination cities in Europe on student.com and Study Abroad Apartments. Using machine learning methodology, we analyse some key tangible and non-tangible features of the properties and explore their relationships with the listed price. We also examine the potential effects of economies of scale through variations in the pricing mechanism for PBSAs and PSAPs. The results show that the non-tangible property attributes have a stronger relationship with student accommodation prices in comparison to the tangible attributes. We also observe that the influence of these non-tangible property features on student accommodation prices is significantly stronger for PSAP properties in comparison to PBSA properties. The results suggest that through the economies of scale mechanism, institutional investors may be able to provide some facilities in their PBSAs at lower costs than PSAP investors and this may result in lower premiums for these facilities as reflected in the pricing. From a methodological point of view, we show that the use of asset features and historic pricing trends can enable the training of various supervised machine learning algorithms which in turn can improve asset pricing, taking account of national and non-institutional investment types.