Abstract:
We propose a flexible framework that allows for the relationship between housing prices and their determinants to vary over time. Our model incorporates housing-specific characteristics and macroeconomic variables, while accounting for a gradual global trend that reflects the unobserved external environment. We estimate the trend and coefficient curves by local linear estimation and propose a bootstrap procedure for conducting inference. By employing monthly data from the Dutch housing market, covering 60 municipalities from 2006 to 2020, the proposed models show the capability to accurately describe the comovements of housing prices. Our results show strong statistical evidence of time variation in the effects of housing attributes and macroeconomic variables on prices throughout the entire sample period, revealing that the unemployment rate plays a crucial role between approximately 2012 and 2017. The extracted latent global trend reveals a significant influence of the economic environment and takes the shape of a leading indicator of the property market index. Moreover, we find that both the housing characteristics and the external environment explain comparably high proportions of the variation in housing prices, which stresses the importance of including both components in empirical analyses.