Defining spatial housing submarkets: Exploring the case for expert delineated boundaries

Although there are numerous reasons for real estate analysts to construct spatial housing submarkets, there is little clarity about how this might best be done in practice. The existing literature offers a variety of techniques including those based on principal components analysis, cluster analysis and a range of other statistical procedures. This paper asks whether, given their market expertise and their role in disseminating information, shaping search patterns and informing bid formation, real estate agents might offer an effective but less data intensive method of submarket construction. The empirical research is based on an experiment that compares the predictive of different sets of submarket boundaries constructed by using either standard statistical methods or through consultation with real estate agents and other market analysts. The analysis draws on housing transactions data from Istanbul, Turkey. While the results do not demonstrate the outright superiority of any single method, they do suggest that expert-defined boundaries tend to perform at least as well as alternative construction techniques. Importantly, the results suggest that agent-based methods for delineating submarket boundaries might be used with a degree of confidence by real estate analysts and planners in market contexts where rich micro-datasets are not readily available. This has been one of the constraints internationally on wider adoption of submarket boundaries as an analytical tool

Drivers of spatial change in urban housing submarkets

Spatial urban housing submarkets are now widely used constructs. Recent housing market modelling strategies have emphasised the need for flexibility in modelling approaches in order to best accommodate submarkets which account for spatial variations in hedonic prices. But this raises important unanswered questions concerning the stability of submarket structures over time, and the role of housing market dynamics in breaking down or shifting submarket boundaries. The influence of new supply, in particular, may have a stabilising or destabilising effect on differences in hedonic prices, depending on the wider housing market context. In this paper we examine the temporal influence of new supply, intra‐urban migration and socio‐economic change as a means of understanding the impact of key drivers of submarket boundary change. Using the Greater Perth region of Western Australia as a case study, we estimate income elasticities of demand for housing services that vary spatially within the urban area. We find evidence that higher income elasticities, new development, socio‐economic change and intra‐urban migration are associated with changes in the spatial structure of housing prices within the metropolitan housing market

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

Only the best? Exploring cross-border investor preferences in US gateway cities

Despite heady growth in cross-border investment into commercial real estate over recent decades, there are few studies that examine differences in investment preferences between domestic and cross-border investors at a micro level. We address the gap by examining the characteristics of assets acquired by cross border investors in six major US metro areas, comparing them with the purchases made by US investors in those same areas. Our study uses data on more than 67 500 transactions recorded by Real Capital Analytics (RCA) over the period from Q1 2003 to Q3 2016. As well as examining cross-border investors in aggregate, we isolate and examine purchases by investors from each of the four principal source nations for cross-border real estate investment in these cities. This is important since treating cross-border investors as a single group may obscure important differences between them. We employ multilevel logit techniques and we find across a number of specifications that cross-border investors prefer larger assets, newer assets and CBD locations regardless of nationality. However, temporal and sectoral patterns of investment, as well as evidence for return chasing behavior, vary with the nationality of investor being studied

Modelling UK house prices with structural breaks and conditional variance analysis

This paper differs from previous research by examining the existence of structural breaks in the UK regional house prices as well as in the prices of the different property types (flats, terraced, detached and semi-detached houses) in the UK as a whole, motivated by the uncertainty in the UK housing market and various financial events that may lead to structural changes within the housing market. Our paper enhances the conventional unit root tests by allowing for structural breaks, while including structural break tests strengthens our analysis. Our empirical results support the existence of structural breaks in the mean equation in seven out of thirteen regions of the UK as well as in three out of four property types, and in the variance equation in six regions and three property types. In addition, using a multivariate GARCH approach we examine both the behaviour of variances and covariances of the house price returns over time. Our results have significant implications for appropriate economic policy selection and investment management