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This paper using evidence from the Spanish housing market contributes significantly to the debate concerning the different results obtained from house price indices depending on the method used to build the index. Utilising a large database over the period 1994 to 2012, the paper constructs a time dummy hedonic index (HD) and an imputed hedonic index using a Laspeyres approach (HI), and compares the different effect on the price index evolution. The paper discusses control by quality changes and identifies those attributes experiencing structural changes over the analysis period, identified by the HI index but not by the HD index. Results indicate that changes in quality stem from socio-demographic conditions rather than changes to housing quality (other than size). The paper also shows that improvements in neighbourhood quality rather than change in a 'typical house' affects house price and argues that these considerations are important in both the method selected to calculate house price indices and the application of the methodology to estimate price changes. [ABSTRACT FROM AUTHOR]

This paper is concerned with spatial effects of time on the market for residential property and time varying relationships using a dataset of properties from the Adelaide metropolitan area, Australia, during the period 2002–2011. The analysis firstly considers the spatial dependence in time on the market and secondly extends the analysis to a space-time model using 2SLS regression. The findings demonstrate the complexity in spatial analysis with results indicating a random distribution of time on the market in 86% of observations a pattern that is consistent over time. Spatial autocorrelation is shown to increase time on the market in the subject property while spatial error decreases time on the market in the subject property suggesting a high level of market transparency and improved liquidity. The compensating or nullifying effects of both types of spatial association is shown to contribute to the random distribution observed in time on the market. A strong explanatory capacity of the business cycle suggests that economic drivers are leading time on the market rather than prices. [ABSTRACT FROM AUTHOR]

This paper begins by identifying the growth in female-headed households in Australia. Despite this increase, it is argued that females still lag males in terms of home ownership rates (HORs) with women in Australia facing similar ownership challenges as those experienced in the UK and the USA. In seeking to establish any dynamic change, the study analyses female home ownership rates in Australia for two points in time, 1998 and 2008. Logit models are used to predict HORs. The results indicate that factors such as household type, income and source of income have an impact on rates of ownership. The paper concludes that female-headed households in Australia show an increasing propensity to purchase which match, or even exceed, those of male-headed households. [ABSTRACT FROM PUBLISHER]

Asking price has a fundamental influence on market behaviour and understanding how attributes affect the perceived price of housing. This paper employs a large database of houses from the Spanish housing market to estimate the role of attributes in asking price formation. STAR methodology and GLM with random effects are used to extract the price of attributes and the spatial and time pattern. Results show that the pricing of attributes varies by geographical region and over time with property size and economic and demographic attributes being the key variables explaining asking price formation. [ABSTRACT FROM PUBLISHER]

Abstract: This paper investigates the relationship between the list and sale price of residential properties over the housing cycle. In down or normal markets the list price generally exceeds the sales price; however, when the housing market is strong, homes sell for more than their list price. This observation is not consistent with the assumptions made in the standard model of home sellers’ search behavior. We consider alternative models. In one, sellers set list prices based on their expectations of future changes in sales prices and the arrival rate of buyers; however, demand shocks occur. This model partially explains our data from the Belfast, U.K. housing market, but it fails to predict the list to sales price ratio during a sustained housing boom. We next describe a model where sellers’ endogenously select their search mechanism depending on the strength of the housing market. We find support for the conjecture that sellers switch to an auction-like model during housing booms. There also is evidence that during a downturn in the market, sellers’ list prices are sticky. [Copyright &y& Elsevier]

Theoretical models of the house selling process have shown the number of bidders involved to be an important factor in explaining sales price; however, empirical models have not included specific variables capturing the dynamic process that occurs during time on the market (TOM). This paper addresses this gap by including explicit bidding variables, as well as TOM in a hedonic pricing model. The results confirm the importance of the number of bidders in understanding the direction of the relationship between price and TOM, identifying that the outcome of multiple bidder sales are more predictable than properties sold with a single bidder. [ABSTRACT FROM AUTHOR]

This paper is concerned with assessing how valuations for mortgage purposes reflect market evidence. Differences between the value obtained through the analysis of comparables and the final assigned value are analysed. The study is undertaken for the Spanish housing market at the peak of the house price boom. High levels of accuracy are apparent but with a tendency to over- rather than undervalue properties. Physical housing variables are shown to have a relatively homogeneous effect, whereas factors relating to the environment and location lead to wider differences between valuations. The effect of characteristics is shown to vary substantially between cities. There is no evidence from the analysis that the property bubble in Spain was driven by inaccuracy in valuations. [ABSTRACT FROM AUTHOR]