Controlling for transactions bias in regional house price indices

Transactions bias arises when properties that trade are not a random sample of the total housing stock. Price indices are susceptible because they are typically based on transactions data. Existing approaches to this problem rely on Heckman-type correction methods, where a probit regression is used to capture the differences between properties that sell and those that do not sell in a given period. However, this approach can only be applied where there is reliable data on the whole housing stock. In many countries—the UK included—no such data exist and there is little prospect of correcting for transactions bias in any of the regularly updated mainstream house price indices. Thispaper suggests a possible alternative approach, using information at postcode sector level and Fractional Probit Regression to correct for transactions bias in hedonic price indices based on one and a half million house sales from 1996 to 2004, distributed across 1200 postcode sectors in the South East of England

What account for the differences in rent-price ratio and turnover rate? A search-and-matching approach

We build an on-the-house-search model and show analytically that the rent-to-price ratio (or rental yield) and turnover rate, which are frequently used metrics for the housing market, are jointly determined in equilibrium. We therefore adopt a simultaneous equation approach on matched sale-rental pairs in our empirical investigation, as a housing unit cannot be owner-occupied and renter-occupied at the same time. Our empirical results confirm a higher turnover rate is associated with a lower rent-to-price ratio, as predicted by the model. Furthermore, our results suggest a form of “dichotomy” in the empirical determinants of rental yield and turnover at the real-estate-development (RED) level: the demographic structure, and past return performance affect its turnover rate, while popularity, human capital environment, mortgage burden, and long run rent growth determine the rental yield. No evidence of “thick market effect” is found. The robustness of our results are established through a series of tests. In addition to these findings, our tractable search-theoretic model, a ranking of more than 130 RED in Hong Kong based on the popularity index we construct, and the estimated brand-premium for different major real estate developers may also carry independent research and practical interests