Measuring House Price Bubbles

We thank John Clapp, Martijn Dröes, Mika Kortelainen, and Song Shi for helpful comments. Financial support from the Academy of Finland, the OP‐Pohjola Group Research Foundation, the Kluuvi Foundation, and the Emil Aaltonen Foundation is gratefully acknowledged.

Real estate agency practice and profitability : an analysis of house sales and agency profitability in Sydney

Large cities provide a broad range of residential property types, as well as a range of socio-economic locations. This results in a significant variation in residential property prices across both the city itself and the individual suburbs. The only constant across such a diverse range of residential property is the need for the majority of residential property owners to employ the services of a real estate agent to sell their property or to purchase a residential property. This paper will analyse the Sydney residential property market over the period 1994 to 2002 to determine the change in real estate offices numbers over the period, the profitability of real estate agency offices based on the residential house price performance of houses and units in these specific locations and the extent of changing residential house prices on agency profitability. Suburbs have been selected to provide a full range of housing types, socio-economic areas, older established and developing residential suburbs and location from the

The impact of infrastructure charges on house prices in Australia

Developer paid fees or charges are a commonly used mechanism for local governments to pay for new infrastructure. However, property developers claim that these costs are merely passed on to home buyers, with adverse effects to housing affordability. Despite numerous government reports and many years of industry advocacy, there remains no empirical evidence in Australia to confirm or quantify this passing on effect to home buyers. Hence there remains no data from which governments can base policy decision on, and the debate continues. This paper examines the question of the impact of infrastructure charges on housing affordability in Australia. It presents the findings of a hedonic house price model that provides the first empirical evidence that infrastructure charges do increase house prices in Australia. This research is consistent with international findings, that support the proposition that developer paid infrastructure charges are passed on to home buyers and are a significant contributor to increasing house prices and reduced housing affordability.

Submission to House of Representatives Standing Committee on Economics Inquiry into Home Ownership

This paper empirically examines the effect of current tax policy on home ownership, specifically looking at how developer contributions impact house prices. Developer contributions are a commonly used mechanism for local governments to pay for new urban infrastructure. This research applies a hedonic house price model to 4,699 new and 25,053 existing house sales in Brisbane from 2005 to 2011. The findings of is research are consistent with international studies that support the proposition that developer contributions are over passed. This study has provided evidence that suggest developer contributions are over passed to both new and existing homes in the order of around 400%. These findings suggest that developer contributions are thus a significant contributor to increasing house prices, reduced housing supply and are thus an inefficient and inequitable tax. By testing this effect on both new and existing homes, this research provides evidence in support of the proposition that not only are developer contributions over passed to new home buyers but also to buyers of existing homes. Thus the price inflationary effect of these developer contributions are being felt by all home buyers across the community, resulting in increased mortgage repayments of close to $1,000 per month in Australia. This is the first study to empirically examine the impact of developer contributions on house prices in Australia. These results are important as they inform governments on the outcomes of current tax policy on home ownership, providing the first evidence of its kind in Australia. This is an important contribution to the tax reform agenda in Australia.

Topics in Spatial Econometrics - With Applications to House Prices

Topics in Spatial Econometrics — With Applications to House Prices Spatial effects in data occur when geographical closeness of observations influences the relation between the observations. When two points on a map are close to each other, the observed values on a variable at those points tend to be similar. The further away the two points are from each other, the less similar the observed values tend to be. Recent technical developments, geographical information systems (GIS) and global positioning systems (GPS) have brought about a renewed interest in spatial matters. For instance, it is possible to observe the exact location of an observation and combine it with other characteristics. Spatial econometrics integrates spatial aspects into econometric models and analysis. The thesis concentrates mainly on methodological issues, but the findings are illustrated by empirical studies on house price data. The thesis consists of an introductory chapter and four essays. The introductory chapter presents an overview of topics and problems in spatial econometrics. It discusses spatial effects, spatial weights matrices, especially k-nearest neighbours weights matrices, and various spatial econometric models, as well as estimation methods and inference. Further, the problem of omitted variables, a few computational and empirical aspects, the bootstrap procedure and the spatial J-test are presented. In addition, a discussion on hedonic house price models is included. In the first essay a comparison is made between spatial econometrics and time series analysis. By restricting the attention to unilateral spatial autoregressive processes, it is shown that a unilateral spatial autoregression, which enjoys similar properties as an autoregression with time series, can be defined. By an empirical study on house price data the second essay shows that it is possible to form coordinate-based, spatially autoregressive variables, which are at least to some extent able to replace the spatial structure in a spatial econometric model. In the third essay a strategy for specifying a k-nearest neighbours weights matrix by applying the spatial J-test is suggested, studied and demonstrated. In the final fourth essay the properties of the asymptotic spatial J-test are further examined. A simulation study shows that the spatial J-test can be used for distinguishing between general spatial models with different k-nearest neighbours weights matrices. A bootstrap spatial J-test is suggested to correct the size of the asymptotic test in small samples.

Forecasting annual inflation with seasonal monthly data: using levels versus logs of the underlying price index

This paper investigates whether using natural logarithms (logs) of price indices for forecasting inflation rates is preferable to employing the original series. Univariate forecasts for annual inflation rates for a number of European countries and the USA based on monthly seasonal consumer price indices are considered. Stochastic seasonality and deterministic seasonality models are used. In many cases, the forecasts based on the original variables result in substantially smaller root mean squared errors than models based on logs. In turn, if forecasts based on logs are superior, the gains are typically small. This outcome sheds doubt on the common practice in the academic literature to forecast inflation rates based on differences of logs.