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

Risk perception and vulnerability of value: a study in the context of commercial property sector

© 2016 The Author(s). Published by Vilnius Gediminas Technical University (VGTU) Press, and Taylor & Francis. The research was developed linking the impact of flood risk on utility, desirability and marketability related to vulnerability of commercial property value. Likert style questionnaire survey was conducted to obtain data from flood affected and un-affected respondents across different designated flood risk zones on key business and perception variables among two groups of business property holders in England. The responses were analysed through a spatial vulnerability model to illustrate the distribution of the vulnerability of value of properties among flood plain business holders on a GIS platform. Majority of respondents perceived that utility of properties may be hampered by flooding and subsequently have an impact on value for property at risk. Those with flood experience gave greater weight to their specific business needs such as the prime location and expected income level than those without flood experience. The implication of the study lies in understanding that flood risk perceptions can shape actions of people at risk towards future increase in resilience having strategic impact on value of property saleability in the future

Assessing External Effects of City Airports: Land Values in Berlin

This paper employs a hedonic price model to explain standard land values in Berlin. Impact on land values is assessed for the two city airports situated in Berlin, Germany, Tempelhof and Tegel. Empirical results confirm expectations about the impact of various attributes on land values. Areas exposed to noise pollution of downtown airport Tempelhof sell at a discount of approximately 5-9% within a distance of 5000 m along the air corridor. No significantly negative impact was found for land values around Tegel Airport, which is located in a central, but less densely populated, area. Market access indicators created for all three Berlin airports in operation, including Berlin Schoenefeld International Airport, reveal clear location advantages in terms of accessibility of Tempelhof and Tegel compared to Schoenefeld Airport, where the new Berlin Brandenburg International Airport is about to be developed

Further evidence on the (in-) efficiency of the U.S. housing market

Extending the controversial findings from relevant literature on testing the efficient market hypothesis for the U.S. housing market, the results from the monthly and quarterly transaction-based Case-Shiller indices from 1987 to 2009 provide further empirical evidence on the rejection of the weak-form version of efficiency in the U.S. housing market. In addition to conducting parametric and non-parametric tests, we apply technical trading strategies to test whether or not the inefficiencies can be exploited by investors earning excess returns. The empirical findings suggest that investors might be able to obtain excess returns from both autocorrelation- and moving average-based trading strategies compared to a buy-and-hold strategy