Modelling regional house prices
We develop a panel model for regional house prices, for which both the cross-section and the time series dimension is large. The model allows for stochastic trends, cointegration, cross-equation correlations and, most importantly, latent-class clustering of regions. Class membership is fully data-driven and based on the average growth rates of house prices, and the relationship of house prices with economic growth. We apply the model to quarterly data for the Netherlands. The results suggest that there is convincing evidence for the existence of two distinct clusters of regions with pronounced differences in house price dynamics.
|Keywords||cointegration, cross section dependence, house prices, ripple effect|
|JEL||Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions (jel C21), Models with Panel Data (jel C23), Forecasting and Other Model Applications (jel C53)|
|Persistent URL||dx.doi.org/10.1080/00036840903085089, hdl.handle.net/1765/22208|
|Series||Econometric Institute Reprint Series|
van Dijk, A, Franses, Ph.H.B.F, Paap, R, & van Dijk, D.J.C. (2011). Modelling regional house prices. Applied Economics, 43(17), 2097–2110. doi:10.1080/00036840903085089