An Analysis of Spatial Autocorrelation in Hong Kong’S Housing Market

Abstract

Spatial autocorrelation is commonly found in the Hedonic Pricing model for real estate prices, but little is known about the time window within which nearby sales are used to form current prices. The primary objective of this study is to examine how spatial autocorrelation varies with the length of this time window. We hypothesize that more recent sales have a stronger influence than earlier sales on current prices, so a shorter time window should induce stronger spatial autocorrelation. We propose a Spatial Hedonic Pricing (SHP) model to test our hypothesis. Based on 15,500 transactions of residential units in Taikooshing, Hong Kong from 1992 to 2006, we conclude that while positive spatial autocorrelation is present in housing prices, its magnitude increases when the reference period of past sales becomes shorter. The latter is a new finding in the spatial hedonic literature that not only confirms the importance of timeliness in weighting nearby housing price information, but also calls for further research on how fast such information expires in different markets.