Spatial Variation in the Determinants of House Prices and Apartment Rents in China

Dean M. Hanink, Robert G. Cromley, Avraham Y. Ebenstein

Research output: Contribution to journalArticlepeer-review

49 Scopus citations


This paper provides an examination of China's residential real estate market at the county level using data from that country's 2000 census. The market is a new one, having only been fully established in 1998. The analysis in the paper is in the form of an aggregate (county-level) hedonic model specified in two versions. Global parameters results are estimated using spatial error model specifications while more local effects are estimated by geographically weighted regression. Global results are typical in that structural characteristics such as floor space and contextual characteristics such as level of in-migration are important in residential prices. Local results, however, indicate significant spatial variation in the effect of both structural amenities and locational context on housing prices. In a simpler specification, rents are shown to respond positively to both median house prices levels and the supply of apartments available at market prices, but also with significant spatial variation across China.

Original languageAmerican English
Pages (from-to)347-363
Number of pages17
JournalJournal of Real Estate Finance and Economics
Issue number2
StatePublished - Aug 2012


  • China
  • Geographically weighted regression
  • Hedonic model
  • Housing market
  • Spatial regression


Dive into the research topics of 'Spatial Variation in the Determinants of House Prices and Apartment Rents in China'. Together they form a unique fingerprint.

Cite this