Abstract
George Akerlof’s asymmetric information theory explains why lemons are rarely, if at all, transacted. We extend his theory to explain liquidity in the second-hand real estate market. The idea is to decompose real estate into two components: land and the building structure. While sellers may know more about the quality of their structures than buyers, information on land, predominantly its locational attributes, is much more transparent. Without assuming any credit constraints or loss aversion behaviour, our information asymmetry model shows that: 1) the liquidity of real estate increases with the share of its land value; 2) there is a positive relationship between real estate prices and turnover rates when land supply is more inelastic than the supply of structures; 3) the positive relationship is stronger when the land value component gets smaller; and 4) while the availability of first-hand real estate may divert demand away from the second-hand market, such a substitution effect is weaker when the land value component is large. These four implications were confirmed with panel data analysis using Hong Kong’s housing transactions from 1992 to 2008 across 50 districts.
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Notes
In Hong Kong, professional inspection or certification is not common in the condo market because the cost involved is very high. Apart from professional fees, many building problems (e.g. the testing of water seepage) have to be inspected from outside a condo unit, and prior permission has to be sought from neighbours and tenants (if any).
Levitt and Syverson (2008) examined a principal-agent problem, in which brokers distorted information to induce their clients to sell their houses quickly, but at a lower price. The current study examines asymmetric quality information between buyers and sellers. Brokers may have a good sense of market sentiment and individual preferences, but they do not necessarily know more about the quality of individual properties.
Here we assume that there are only two types of product: high and low quality. Their shares (w and 1-w) are always larger than zero.
As LPGk is a sample estimate from another regression, it may measure %L with a sampling error. The consequence is that the coefficients of the regressions in Eqs. 6a and 6b are still consistent, but their standard errors are incorrect (Murphy and Topel 1985). Correcting for the standard errors, however, does not appear to change our results in any significant way. This is because LPGk was estimated from a huge sample (see the “Data” section) that substantially reduces the problem of sampling error.
These expensive properties are mostly located in high land value districts (hence, high LPG k ) as a result of the high land-to-building value ratio in Hong Kong (see also an illustration in the “Data” section).
An alternative to first differencing is a fixed or random effects model. Neither model, however, was employed because some variables, notably the property price index, were not stationary in level terms.
The housing price index of one of the largest housing estates (Mei Foo) showed a 100-fold increase from 1969 to 2008, while the tender price index grew from 100 in 1970 to only 140 in 2008 (see http://www.dlsqs.com/).
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Acknowledgements
This project was financially supported by the General Research Fund (Project Reference: HKU 755210). We are grateful for the comments from participants at the Building and Real Estate Workshop at Hong Kong Polytechnic University and the Asia Pacific Real Estate Research Symposium at the University of Southern California.
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Wong, S.K., Yiu, C.Y. & Chau, K.W. Liquidity and Information Asymmetry in the Real Estate Market. J Real Estate Finan Econ 45, 49–62 (2012). https://doi.org/10.1007/s11146-011-9326-z
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DOI: https://doi.org/10.1007/s11146-011-9326-z