Office Rent Determinants in the Finnish Commercial Property Market

Abstract

More and more foreign investors have entered the Finnish property market since 2002. The trend of investing in Finnish commercial properties is strongly increasing. The foreign investors have particularly favoured office investment in Helsinki metropolitan area because of offices perceived relatively low risks and relatively consistent demand in the property market. The increase of attractiveness facilitates both practitioners and academics to examine a deeper understanding of office properties, their valuable attributes and rent determinants.

The objective of this thesis was to apply a theoretical analysis to identify the significant rent determinants for office properties. The study consisted of literature review and empirical study. The literature review included the study of macroeconomic-related determinants, building characteristics determinants, location determinants, and model selection. These studies were mainly concentrated on academic researches in US and UK, and found out that location, building age, building size, vacancy rate and leases were most important determinants for office rent.

In the empirical study, a modified rating model was formed based on the analysis of previous research. The model mainly contained five variables: macroeconomic factor, location, building characteristics, potential, and lease agreement. The model was tested through four offices W, X, Y, and Z. As author assumed that an office with a higher rating should have a higher rent, and an office with a lower rating should have a lower rent. The research results showed exactly same as author's assumption. Furthermore, the research results confirmed that location, building age and building size were most important rent determinants for office properties.

Author believes that the modified rating model is feasible both in theoretical research and practice. Furthermore, author suggests that the rating model can be added more different variables or factors with different weights in order to achieve a better rating model. This can be done in practice with more different office properties in different market areas.