Handbook on Residential Property Price Indices Chapter 10: Data Sources

Chapter 10: Data Sources Chapter 10 examines the different sources of data that can be used for constructing RPPIs Such as newspapers, real estate agents, mortgage companies, property registers, and tax offices (mainly readily available) It focuses mainly on price data Data sources for prices often act as a constraint. For example Timeliness Revisions Techniques available to quality adjust for houses of different sizes & locations Final section discusses situation confronted in many developing countries where Data are scarce; Ownership is a fuzzy notion; No easy solutions Input prices as an alternative?

Chapter 10: Data Sources Administrative information is main data source for most compilers A function of the house price data-sets generated by a country’s legal & administrative processes associated with buying a house Resulting index numbers can vary according to Data source e.g. purchase price when financed by loan versus purchase price for cash sale Can effect price levels & trends The point in the house purchasing process at which the price is measured E.g. Advertised price, initial offer price or actual purchase prices Lack of detail can be problematic For example, the inability to quality adjust - particularly problematic where there is a lack of homogeneity, as in the case of the residential property market (e.g. Hedonics &/or mix-adjustment) Purpose designed surveys costly Unless conducted for other purposes e.g. Property valuations for taxation purposes (but valuations are not purchase prices)

Chapter 10: Data Sources – administrative data generated by house sales/purchases Chapter 10 lists the relative advantages/disadvantages of different data sources Definition, coverage (e.g. mortgage purchases only), timeliness, revisions, reliability, detail (e.g. for mix/quality adjustment) Multiple data sources can lead to competing indices from different sources Different trends in house prices Key to successful use of administrative data Detailed knowledge of data collection processes & operational systems & user needs

Chapter 10: Data Sources To gauge fitness-for-purpose requires an evaluation against user needs Chapter 10 lists of desirable properties for a residential property price index Frequency; Revisions; Coverage; Quality; Timeliness; Detail for quality adjustment and mix-adjustment; Comparability (International comparisons) Data integration? E.g. Model relationship between valuations by mortgage lenders & final transaction price recorded by Land Registry

Chapter 10: Data Sources Diagram: House purchase timeline and house price indices (UK) Source: Bank of England and ODPM

Chapter 10: Data Sources Asking price More timely but uncertainty & haziness regarding data sources & uncertain relationship between asking price and selling price Initial offer price accepted by seller: mortgage companies Uncertain relationship between initial offer price & transaction price & between mortgage versus cash purchases Valuation price for loan: mortgage companies Valuations tend to be cautious in downturn detailed survey of the property reveals that substantial repairs are necessary Process of re-negotiation? Final transaction price: mortgage companies Not always recorded by mortgage lenders

Chapter 10: Data Sources Final transaction price: administrative data – property registers and tax offices trade-off between timeliness and accuracy Valuation price for taxation and payment for local services: tax offices Can be out-of-date & general approximations Expert opinion (soft information): surveys of estate agents organisations, other professional bodies and their members Objective but judgemental

Chapter 10: Data Sources – & finally expenditure weights Different weighting schemes produce price indices which measure different concepts of house prices and house price movements Whether an index is “stock” or “transaction” weighted Whether volume or value weights are used Important to have clear understanding of what the target measure So that the indices can be evaluated against the target measure to determine fitness-for-purpose

Chapter 10: Data Sources The End