Housing price dispersion in the presale market

Abstract

Sale before completion (i.e. presale) is a common practice that real estate developers use to sell residential units. Since presale buyers are unable to inspect uncompleted units, developers may take advantage of asymmetric information and release information about quality to the market selectively. The search theory also suggests that incomplete pricing information, especially for new products, will induce a less competitive market that is characterised by dispersed presale prices. Would price dispersion be reduced if developers were required to provide more quality and pricing information? In this study, we argue that this is not necessarily the case. We conduct a natural experiment using a new information disclosure ordinance governing first-hand residential sales in the Hong Kong SAR, China. We find that the ordinance reduced the price dispersion of presale units with asymmetric information about property quality, but increased their price dispersion when limited pricing information (e.g. thin trading volume) was available in the neighbourhood. As a critical test, we further show that the ordinance increased price dispersion even more after the units were completed. This suggests that the ordinance has indeed made presale pricing more difficult because developers are no longer allowed to use different strategies to test market demand.

Keywords:

• Price dispersion
• presale housing market
• pricing information
• quality information
• natural experiment

Notes

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1 The separation of ‘informed’ and ‘uninformed’ sellers in the real estate market can be found in Deng et al. (2012).

2 In the previous clearinghouse models, firms’ listing decisions are exogenous.

3 Proof of these properties for this generalised information clearinghouse model can be obtained from Baye, Morgan, and Scholten (2006, 22–23).

4 This argument follows Varian (1980) in which price dispersion is mainly driven by the variation in consumers’ information access costs.

5 For more details about the linkage between housing price dispersion and macroeconomic factors in Hong Kong, see Leung, Leong, and Wong (2006).

6 The adjustment is made by deflating the transaction price with the district specific repeated-sales prices indices (Chau et al. 2005). More specifically, a semi-log form of OLS equation of ${\text{ln\hspace{0.17em}}\mathit{P}}_{it}= {\sum }_{j=1}^J{\beta }_j{X}_{\mathit{jit}}+ {\epsilon }_{\mathit{ijt}}$ is specified, where $\ln P_{it}$ denotes the natural logarithm of the deflated transaction price of property i at time t $(i=1,...,n; t=1,...T),$ ${\beta }_j$ represents the implicit prices for the j^th property attributes $X_{\mathit{jit}}$ of which $j=1,...,J;$ and ${\epsilon }_i$ denotes the error term with mean zero and variance ${\sigma }^2.$ This error term represents the deviation of the implicit price of a particular property i from its shadow price.

7 In the probability theory, the geometric coefficient of variation (GCV) is a more standardised measure of dispersion of a frequency distribution given the data are log-normally distributed. We will further discuss that in our empirical setup. For the time being, variance is used for our preliminary analysis.

8 Some other studies used standard deviation or coefficient of variation to measure price variation. Our results are robust to such conventional price dispersion measures.

9 It might be argued that higher price dispersion can be interpreted as price discrimination, but there is no reason to believe that the ability to discriminate is strengthened after developers are more restrained by the Ordinance.

Additional information

Funding

This project was financially supported by the General Research Fund [Project Reference: HKU 17201515] Research Grants Council, University Grants Committee.