# 13-171/VIII (2013-10-18)

Author(s)
Marco Helbich, University of Heidelberg, Germany; Wolfgang Brunauer, UniCredit Bank Austria AG, Austria; Eric Vaz, Ryerson University, Canada; Peter Nijkamp, VU University Amsterdam
Keywords:
Spatial heterogeneity, real estate, house price models
JEL codes:
R1

This discussion paper led to an article in Urban Studies (2014). Volume 51, issue 2, pages 390-411.

Modeling spatial heterogeneity (SH) is a controversial subject in real estate economics. Single-family-home prices in Austria are explored to investigate the capability of global and locally weighted hedonic models. Even if regional indicators are not fully capable to model SH and technical amendments are required to account for unmodeled SH, the results emphasize their importance to achieve a well-specified model. Due to SH beyond the level of regional indicators, locally weighted regressions are proposed. Mixed geographically weighted regression (MGWR) prevents the limitations of fixed effects by exploring spatially stationary and non-stationary price effects. Besides reducing prediction errors, it is concluded that global model misspecifications arise from improper selected fixed effects. Reported findings provide evidence that SH of implicit prices is more complex than can be modeled by regional indicators or purely local models. The existence of both stationa ry and non-stationary effects imply that the Austrian housing market is economically connected.