Investigating the socioeconomic and demographic principal components (SDPC) impact on the real estate market price in Finland : (focused markets: Helsinki, Espoo, Vantaa, Tampere, and Turku, 2013-2020)

Abstract

This thesis investigates Finland's real estate market's socioeconomic and demographic principal components (SDPC) and their evolution in the five most populated cities, Helsinki, Espoo, Vantaa, Tampere, and Turku, from 2013 to 2020. The economy and demography evolution in the cities mentioned above has been investigated.

This thesis aims to create a predictive housing price model based on the socioeconomic and demographic factors influencing property prices in the focused cities. The Principal Component Regression model was applied in this thesis based on the study background and thesis goals.

The study results indicate that socioeconomic and demographic principal components significantly impact the property price in the focused markets. Accordingly, this study achieved its goal by developing a predictive housing price model that considers socioeconomic and demographic components. Running K-fold cross-validation, the result indicates that the predictive model with one principal component outperformed the other models.