Hedonic house prices and spatial quantile regression
Despite its long history, hedonic pricing for housing valuation remains an active research area, and applications of new estimation methods continually push research frontiers. However, housing studies regarding Chinese cities are limited because of the short history of China’s free housing market. Such studies may, nonetheless, provide new insights given the nation’s current transitional stage of economic development. Therefore, this research makes use of publicly accessible sources to construct a new micro-dataset for an emerging Chinese city, Changsha, and it incorporates quantile regression with spatial econometric modeling to examine how implicit prices of housing characteristics may vary across the conditional distribution of house prices. Substantial variations are found, and the intuitions and implications are discussed. Additionally, the spatial dependence exhibits a U-shape pattern. The dependence is strong in the upper and lower parts of the response distribution, but it is little in the medium range.
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