A New Approach for Constructing Home Price Indices in China: The Pseudo Repeat Sales Model

Due to data and methodology constraints, there is a lack of good quality-controlled residential price indices publicly available in China. New home sales account for quite a large share of total home sales (87% in 2010) in Chinese cities, As a result, the standard repeat sales approach cannot be employed, as a new housing unit only appears once on the market. The hedonic method may be more suitable in principle, but it is vulnerable to an omitted variables problem which may be more significant in Chinese cities due to extremely dynamic urban spatial structure development and fast infrastructure construction.Taking advantage of a unique feature of residential development in Chinese cities, we develop a “pseudo repeat sale” model (ps-RS) to construct more reliable quality-controlled price indices for newly-constructed homes. The new homes are developed in the form of residential complexes. Each complex is developed by a single developer and contains a number of high-rise residential buildings. Each housing unit within the same complex shares the same location and community attributes, as well as similar physical characteristics (such as structure type, architecture style, housing age, etc). Of course, there may still be important differences in unit size, number of bedrooms, floor level within the high-rise, and the direction the main bedroom faces. Based on specific criteria, we match two very similar new sales within a complex to create a “pseudo-pair. ” We are able to generate a vast number of such pairs, many more than in traditional repeat sales models. By regressing the price differential onto the within-pair differentials in unit-specific physical attributes as well as the usual repeat-sales time dummy variables corresponding to the index periods (locational and community variables are cancelled out), we are able to construct a ps-RS price index for new homes. This ps-RS price index approach not only addresses the problem of lack of repeat-sales data and the omitted variables problem in the hedonic, but also addresses the traditional problems with the classical repeat-sales model in terms of small sample sizes or sample selection bias. Another advantage of this index is its transparency and ease of understandability for better communication with non-specialized constituencies (government and private sector policy makers, investors, and analysts). We test the approach using a large-scale micro transaction data set of new home sales from January 2005 to June 2011(469,070 observations) in Chengdu, Sichuan Province. We estimate our ps-RS indices and compare them with a corresponding standard hedonic index. The two indexes show similar overall price appreciation patterns, but the ps-RS index has less volatility and larger first-order autocorrelation than the hedonic index, suggesting that the ps-RS exhibits less random estimation error. The ps-RS approach may be suitable for any rapidly urbanizing country in which new home sales dominate the housing market and where the new housing stock is constructed in large-scale complexes consisting of many relatively homogeneous individual units.