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

Short-Range B-site Ordering in Inverse Spinel Ferrite NiFe2O4

The Raman spectra of single crystals of NiFe2O4 were studied in various scattering configurations in close comparison with the corresponding spectra of Ni0.7Zn0.3Fe2O4 and Fe3O4. The number of experimentally observed Raman modes exceeds significantly that expected for a normal spinel structure and the polarization properties of most of the Raman lines provide evidence for a microscopic symmetry lower than that given by the Fd-3m space group. We argue that the experimental results can be explained by considering the short range 1:1 ordering of Ni2+ and Fe3+ at the B-sites of inverse spinel structure, most probably of tetragonal P4_122/P4_322 symmetry.Comment: 10 pages, 5 figures, 6 table

Synchronisation and commonalities in metropolitan housing market cycles

This paper examines the degree of commonalities present in the cyclical behavior of the eight largest metropolitan housing markets in Australia. Using two techniques originally in the business cycle literature we consider the degree of synchronization present and secondly decompose the series’ into their permanent and cyclical components. Both empirical approaches reveal similar results. Sydney and Melbourne are closely related to each other and are relatively segmented from the smaller metropolitan areas. In contrast, there is substantial evidence of commonalities in the cyclical behavior of the remaining cities, especially those on the Eastern and Southern coasts of Australia

UK Housing Market: Time Series Processes with Independent and Identically Distributed Residuals

The paper examines whether a univariate data generating process can be identified which explains the data by having residuals that are independent and identically distributed, as verified by the BDS test. The stationary first differenced natural log quarterly house price index is regressed, initially with a constant variance and then with a conditional variance. The only regression function that produces independent and identically distributed standardised residuals is a mean process based on a pure random walk format with Exponential GARCH in mean for the conditional variance. There is an indication of an asymmetric volatility feedback effect but higher frequency data is required to confirm this. There could be scope for forecasting the index but this is tempered by the reduction in the power of the BDS test if there is a non-linear conditional variance process

Affordability targets: Implications for Housing Supply

This report presents the results of an econometric modelling project, concerned with regional housing affordability, conducted for the ODPM between November 2004 and April 2005. The key outputs of the project are not just this report, but the model itself, the details of which are set out in the accompanying Technical Appendix, available via the ODPM website: www.odpm.gov.uk/housing. The team for the project was large, including fifteen individuals from nine organisations. The project was directed from the University of Reading. In addition to the team, the work was improved by help from an advisory group and a user group, consisting of members drawn from both central government and from the wider academic and policy communities

Systemic Risk and the Ripple Effect in the Supply Chain

Supply chains are highly complex systems, and disruptions may ripple through these systems in unexpected ways, but they may also start in unexpected ways. We investigate the causes of ripple effect through the lens of systemic risk. We derive supply chain systemic risk from the finance discipline where sources of risk are found in systemic risk-taking, contagion, and amplification mechanisms. In a supply chain context, we identify three dimensions that influence systemic risk, the nature of a disruption, the structure, and dependency of the supply chain, and the decision-making. Within these three dimensions, there are several factors including correlation of risk, compounding effects, cyclical linkages, counterparty risk, herding behavior, and misaligned incentives. These factors are often invisible to decision makers, and they may operate in tandem to exacerbate ripple effect. We highlight these systemic risks, and we encourage further research to understand their nature and to mitigate their effect

Identifying house price diffusion patterns among Australian state capital cities

Prior research supports the proposition that house price diffusion shows a ripple effect along the spatial dimension. That is, house price changes in one region would reflect in subsequent house price changes in other regions, showing certain linkages among regions. Using the vector autoregression model and the impulse response function, this study investigates house price diffusion among Australia\u27s state capital cities, examining the response of one market to the innovation of other markets and determining the lagged terms for the maximum absolute value of the other markets\u27 responses. The results show that the most important subnational markets in Australia do not point to Sydney, rather towards Canberra and Hobart, while the Darwin market plays a role of buffer. The safest markets are Sydney and Melbourne. This study helps to predict house price movement trends in eight capital cities.<br /

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

House prices and tourism development in Cyprus: A contemporary perspective

This study investigates the nexus between tourism development and house prices in the Republic of Cyprus over the period spanning from 2005Q1 to 2016Q4. Tourism indicators vis-à-vis tourism arrivals along with other explanatory variables (domestic credit, land area per person, and the consumer price index) are employed in a multivariate Autoregressive Distributed Lag (ARDL)-bound test model. The empirical results indicate a significant evidence of cointegration. Indicatively, an observed adjustment of about 44% from short-run to long-run implies that the model is not relatively slow to adjust to disequilibrium. Importantly, a percent increase in tourism arrivals is observed to cause a rise in house price by about 37%. Expectedly, it is statistically observed that as the land area per person decreases, it is accompanied by a hike in house price. Also, the impacts of domestic credit offered to private enterprises and the consumer price index are different from the results in previous studies. As a policy guide, the government of Cyprus and stakeholders in the tourism and housing sectors should outline a strategy that will ensure the social welfare of people such that housing availability is not hampered by tourism activities