Handbook on Residential Property Price Indices

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For most citizens, buying a residential property (dwelling) is the most important transaction during their lifetime. Residential properties represent the most significant component of households’ expenses and, at the same time, their most valuable assets. The Residential Property Prices Indices (RPPIs) are index numbers measuring the rate at which the prices of residential properties are changing over time. RPPIs are key statistics not only for citizens and households across the world, but also for economic and monetary policy makers. Among their professional uses, they serve, for example, to monitor macroeconomic imbalances and risk exposure of the financial sector.

This Handbook provides, for the first time, comprehensive guidelines for the compilation of Residential Property Price Indexes and explains in depth the methods and best practices used to calculate an RPPI. It also examines the underlying economic and statistical concepts and defines the principles guiding the methodological and practical choices for the compilation of the indices. The Handbook primarily addresses official statisticians in charge of producing residential property price indices; at the same time, it addresses the overall requirement on RPPIs by providing a harmonised methodological and practical framework to all parties interested in the compilation of such indices.

The RPPIs Handbook has been written by leading academics in index number theory and by recognised experts in RPPIs compilation. Its development has been co-ordinated by Eurostat, the statistical office of the European Union, with the collaboration of the International Labour Organization (ILO), International Monetary Fund (IMF), Organisation for Economic Co-operation and Development (OECD), United Nations Economic Commission for Europe (UNECE) and the World Bank.



Data Sources

In practice, because of the high cost of undertaking purpose-designed surveys of house prices, the methods adopted by statistical agencies and others to construct residential property price indices have mainly made use of administrative data, the latter usually being a function of the house price data sets generated by a country’s legal and administrative processes associated with buying a house. The indices so constructed can vary according to the point in the house purchasing process at which the price is measured. For example, the final transaction price or the earlier valuation used for securing a loan could be used as the “price” of the property. Furthermore, different administrative data sets will generally collect information on different sets of characteristics associated with the sales of the properties. These differing information sets will generally affect index compilation methods, often acting as a constraint on the techniques available to quality adjust for houses of different sizes, locations, etc. Thus data sets have historically acted as a constraint on index construction.


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