Measuring a Boom and Bust: The Sydney Housing Market 2001-2006

Hill, Robert J.; Melser, Daniel; Syed, Iqbal A.

doi:10.2139/ssrn.1425247

Cited by 14 publications

(42 citation statements)

References 30 publications

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“…In this case, a repeat-sales index may be biased. This seems to be the situation observed by Hill, Melser and Syed (2009) in their data set for Sydney, and by Shimizu, Nishimura and Watanabe (2010) for Tokyo.…”

Section: Constructing House Price and Rent Indexessupporting

confidence: 70%

How Can One Tell When the Housing Market Is Out of Equilibrium?

Hill

Mascarilla-i-Miro²,

Yegorov³

2013

Proceedings of the 20th Annual European Real Estate Society Conference - Vienna, Austria

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Purpose -One way of detecting departures from equilibrium is by comparing house prices and rents. Here I assess the viability of this approach.Design/methodology -Error-correction models (ECMs) based on price and rent indexes can be used to forecast movements in house prices. The short-term forecasting ability of ECMs is limited though due to the long persistence of departures from equilibrium. ECMs also suffer from the limitation that they do not tell us whether the price-rent ratio is above or below its equilibrium level at any given point in time. To answer this question it is necessary to make cross-section comparisons of prices, rents and user cost (i.e., the cost incurred by owning a house). Findings -A meaningful cross-section comparison requires that prices and rents are quality adjusted.This may require the use of hedonic methods. The equilibrium price-rent ratio (which is derived from the user cost) is difficult to compute since it depends on the expected capital gain. Also, both the actual and equilibrium price-rent ratios differ depending on which segment of the housing market is considered.Originality/value -The housing market, which is prone to booms and busts, can very significantly affect the rest of the economy. Hence it is important that central banks and governments can detect when the housing market is out of equilibrium. I show here how difficult it is to detect such departures.

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Section: Constructing House Price and Rent Indexessupporting

confidence: 70%

How Can One Tell When the Housing Market Is Out of Equilibrium?

Hill

Mascarilla-i-Miro²,

Yegorov³

2013

Proceedings of the 20th Annual European Real Estate Society Conference - Vienna, Austria

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“…Hill et al . () find two such trends in their data set for Sydney, Australia (obtained from Australian Property Monitors). First, the coverage improves over time.…”

Section: Criticisms Of Hedonic Price Indexesmentioning

confidence: 97%

“…These postcode identifiers can take the form of dummy variables. In the case of the Sydney data set, the inclusion of postcode dummies acts to increase the R ‐squared coefficient from about 0.56 to 0.76 (see Hill et al ., ). The hedonic model now takes the following form:

y = Z β + B γ + D δ + ɛ,

where the additional term B is an

H \times (M x 02010; 1)

matrix of postcode dummy variables,

γ

is an

(M x 02010; 1) \times 1

vector of postcode parameters, and M is the number of postcode identifiers.…”

Section: A Taxonomy Of Hedonic Price Indexes For Housingmentioning

confidence: 97%

“…This version of the SAR model is used for example by Cliff and Ord (), Pace and Gilley (), Bell and Bockstael (), and Hill et al . ().…”

Section: Geospatial Data and How To Use It In Hedonic Modelsmentioning

confidence: 97%

“…This seems to be the situation observed by Hill et al . () in their data set for Sydney, Australia over the period 2001–2006. Furthermore, Shimizu et al .…”

Section: The Problem With Measuring Movements In House Prices Using Mmentioning

confidence: 99%

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Hedonic Price Indexes for Residential Housing: A Survey, Evaluation and Taxonomy

Hill

2012

Journal of Economic Surveys

Self Cite

148

122

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Every house is different. It is important that house price indexes take account of these quality differences. Hedonic methods which express house prices as a function of a vector of characteristics (such as number of bedrooms and bathrooms, land area and location) are particularly useful for this purpose. I consider here some developments in the hedonic methodology, as it is applied in a housing context, that have occurred in the last three decades. A number of hedonic house price indexes are now available. However, it is often difficult to see how these indexes relate to each other. For this reason I attempt to impose some structure on the literature by developing a taxonomy of hedonic indexes, and then show how existing indexes fit into this taxonomy. Also discussed are some promising areas for future research in the hedonic field. In particular, greater use needs to be made of spatial econometric and nonparametric methods to exploit the increased availability of geospatial data. The main criticisms of the hedonic approach are evaluated and compared with those of the repeat‐sales and stratified median methods. The overall conclusion is that the advantages of the hedonic approach outweigh its disadvantages.

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A spatial model averaging approach to measuring house prices

Greenaway‐McGrevy

Sorensen

2021

J Spat Econometrics

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We present a novel approach to the estimation of hedonic imputation (HI) price indices for real estate markets using a new Mallows model averaging (MMA) estimator that is robust to spatial dependence. The spatial MMA (SMMA) method is explicitly designed to minimize the quadratic forecast loss of the imputed sales transactions that comprise the HI index when sales transactions are spatially correlated. We apply the SMMA HI approach to a sales transaction dataset for three geographic real estate suburbs of Auckland, New Zealand. The SMMA HI price indices outperform conventional OLS HI methods, exhibiting more accurate out-ofsample prediction and tighter in-sample confidence intervals. The SMMA HI method is expected to offer practitioners enhancements in constant-quality price index accuracy in data sparse environments where model overfitting is a concern, such as high frequency price measurement or highly localized geographies.

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Measuring a Boom and Bust: The Sydney Housing Market 2001-2006

Cited by 14 publications

References 30 publications

How Can One Tell When the Housing Market Is Out of Equilibrium?

How Can One Tell When the Housing Market Is Out of Equilibrium?

Hedonic Price Indexes for Residential Housing: A Survey, Evaluation and Taxonomy

A spatial model averaging approach to measuring house prices

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